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85
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1 #!/usr/bin/env Rscript
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2
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3 suppressPackageStartupMessages(library("optparse"))
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4
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5 option_list <- list(
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109
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6 make_option(c("--adult_mortality"), action="store", dest="adult_mortality", type="integer", help="Adjustment rate for adult mortality"),
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7 make_option(c("--adult_accumulation"), action="store", dest="adult_accumulation", type="integer", help="Adjustment of degree-days accumulation (old nymph->adult)"),
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8 make_option(c("--egg_mortality"), action="store", dest="egg_mortality", type="integer", help="Adjustment rate for egg mortality"),
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112
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9 make_option(c("--input_norm"), action="store", dest="input_norm", help="30 year normals temperature data for selected station"),
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10 make_option(c("--input_ytd"), action="store", dest="input_ytd", default=NULL, help="Year-to-date temperature data for selected location"),
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109
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11 make_option(c("--insect"), action="store", dest="insect", help="Insect name"),
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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"),
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112
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13 make_option(c("--life_stages"), action="store", dest="life_stages", help="Selected life stages for plotting"),
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14 make_option(c("--life_stages_adult"), action="store", dest="life_stages_adult", default=NULL, help="Adult life stages for plotting"),
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15 make_option(c("--life_stages_nymph"), action="store", dest="life_stages_nymph", default=NULL, help="Nymph life stages for plotting"),
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16 make_option(c("--location"), action="store", dest="location", default=NULL, help="Selected location"),
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109
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17 make_option(c("--min_clutch_size"), action="store", dest="min_clutch_size", type="integer", help="Adjustment of minimum clutch size"),
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18 make_option(c("--max_clutch_size"), action="store", dest="max_clutch_size", type="integer", help="Adjustment of maximum clutch size"),
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112
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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"),
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109
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20 make_option(c("--nymph_mortality"), action="store", dest="nymph_mortality", type="integer", help="Adjustment rate for nymph mortality"),
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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)"),
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22 make_option(c("--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"),
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23 make_option(c("--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"),
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112
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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"),
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25 make_option(c("--plot_std_error"), action="store", dest="plot_std_error", help="Plot Standard error"),
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109
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26 make_option(c("--replications"), action="store", dest="replications", type="integer", help="Number of replications"),
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125
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27 make_option(c("--script_dir"), action="store", dest="script_dir", help="R script source directory"),
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109
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28 make_option(c("--young_nymph_accumulation"), action="store", dest="young_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (egg->young nymph)")
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85
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29 )
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30
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111
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31 parser <- OptionParser(usage="%prog [options] file", option_list=option_list);
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32 args <- parse_args(parser, positional_arguments=TRUE);
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33 opt <- args$options;
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85
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34
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122
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35 add_daylight_length = function(temperature_data_frame) {
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36 # Return temperature_data_frame with an added column
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125
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37 # of daylight length (photoperiod profile).
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122
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38 num_rows = dim(temperature_data_frame)[1];
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111
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39 latitude = temperature_data_frame$LATITUDE[1];
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40 daylight_length_vector = NULL;
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85
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41 for (i in 1:num_rows) {
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42 # Get the day of the year from the current row
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43 # of the temperature data for computation.
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111
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44 doy = temperature_data_frame$DOY[i];
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131
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45 daylight_length_vector[i] = get_daylen(doy, latitude);
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85
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46 }
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47 # Append daylight_length_vector as a new column to temperature_data_frame.
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112
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48 temperature_data_frame = append_vector(temperature_data_frame, daylight_length_vector, "DAYLEN");
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111
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49 return(temperature_data_frame);
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85
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50 }
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51
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112
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52 append_vector = function(data_frame, vec, new_column_name) {
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53 num_columns = dim(data_frame)[2];
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54 current_column_names = colnames(data_frame);
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55 # Append vector vec as a new column to data_frame.
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56 data_frame[,num_columns+1] = vec;
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57 # Reset the column names with the additional column for later access.
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58 colnames(data_frame) = append(current_column_names, new_column_name);
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59 return(data_frame);
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102
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60 }
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61
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125
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62 from_30_year_normals = function(norm_data_frame, start_date_doy, end_date_doy, year) {
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122
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63 # The data we want is fully contained within the 30 year normals data.
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64 first_norm_row = which(norm_data_frame$DOY==start_date_doy);
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65 last_norm_row = which(norm_data_frame$DOY==end_date_doy);
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125
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66 # Add 1 to the number of rows to ensure that the end date is included.
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67 tmp_data_frame_rows = last_norm_row - first_norm_row + 1;
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68 tmp_data_frame = get_new_temperature_data_frame(nrow=tmp_data_frame_rows);
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122
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69 j = 0;
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70 for (i in first_norm_row:last_norm_row) {
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71 j = j + 1;
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125
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72 tmp_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
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122
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73 }
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125
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74 return (tmp_data_frame);
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102
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75 }
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76
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131
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77 get_daylen = function(doy, latitude, p=0.8333) {
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78 # The default value for p is from Forsythe 1995.
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79 theta = 0.2163108 + 2 * atan(0.9671396 * tan(0.00860 * (doy - 186)));
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80 phi = asin(0.39795 * cos(theta));
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81 # Compute the length of daylight for the day of the year.
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82 darkness_length = 24 / pi * acos((sin(p * pi / 180) + sin(latitude * pi / 180) * sin(phi)) / (cos(latitude * pi / 180) * cos(phi)));
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83 daylight_length = 24 - darkness_length;
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84 return (daylight_length);
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85 }
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86
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125
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87 get_new_norm_data_frame = function(is_leap_year, input_norm=NULL, nrow=0) {
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88 # The input_norm data has the following 10 columns:
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89 # STATIONID, LATITUDE, LONGITUDE, ELEV_M, NAME, ST, MMDD, DOY, TMIN, TMAX
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90 column_names = c("STATIONID", "LATITUDE","LONGITUDE", "ELEV_M", "NAME", "ST", "MMDD", "DOY", "TMIN", "TMAX");
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91 if (is.null(input_norm)) {
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92 norm_data_frame = data.frame(matrix(ncol=10, nrow));
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93 # Set the norm_data_frame column names for access.
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94 colnames(norm_data_frame) = column_names;
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95 } else {
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96 norm_data_frame = read.csv(file=input_norm, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
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97 # Set the norm_data_frame column names for access.
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98 colnames(norm_data_frame) = column_names;
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99 if (!is_leap_year) {
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100 # All normals data includes Feb 29 which is row 60 in
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101 # the data, so delete that row if we're not in a leap year.
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102 norm_data_frame = norm_data_frame[-c(60),];
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103 # Since we've removed row 60, we need to subtract 1 from
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104 # each value in the DOY column of the data frame starting
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105 # with the 60th row.
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106 num_rows = dim(norm_data_frame)[1];
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107 for (i in 60:num_rows) {
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108 leap_year_doy = norm_data_frame$DOY[i];
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109 non_leap_year_doy = leap_year_doy - 1;
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110 norm_data_frame$DOY[i] = non_leap_year_doy;
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111 }
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112
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112 }
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113 }
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125
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114 return (norm_data_frame);
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111
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115 }
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116
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125
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117 get_new_temperature_data_frame = function(input_ytd=NULL, nrow=0) {
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118 # The input_ytd data has the following 6 columns:
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119 # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
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120 if (is.null(input_ytd)) {
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121 temperature_data_frame = data.frame(matrix(ncol=6, nrow));
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122 } else {
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123 temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
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124 }
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125 colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
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126 return(temperature_data_frame);
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112
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127 }
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111
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128
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124
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129 get_next_normals_row = function(norm_data_frame, year, index) {
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112
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130 # Return the next 30 year normals row formatted
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131 # appropriately for the year-to-date data.
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132 latitude = norm_data_frame[index,"LATITUDE"][1];
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133 longitude = norm_data_frame[index,"LONGITUDE"][1];
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134 # Format the date.
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135 mmdd = norm_data_frame[index,"MMDD"][1];
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136 date_str = paste(year, mmdd, sep="-");
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137 doy = norm_data_frame[index,"DOY"][1];
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138 tmin = norm_data_frame[index,"TMIN"][1];
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139 tmax = norm_data_frame[index,"TMAX"][1];
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131
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140 daylen = get_daylen(doy, latitude);
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141 # Calculate the average temperature based on the
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142 # tmin and tmax values from the 30 year normals data.
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143 temp.profile = get_temperature_at_hour(latitude, row, tmin=tmin, tmax=tmax, daylen=daylen);
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144 mean_temp = temp.profile[1];
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145 avg_temp = temp.profile[2];
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146 return(list(latitude, longitude, date_str, doy, tmin, tmax, daylen, avg_temp));
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102
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147 }
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148
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131
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149 get_temperature_at_hour = function(latitude, row, temperature_data_frame=NULL, tmin=NULL, tmax=NULL, daylen=NULL) {
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111
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150 # Base development threshold for Brown Marmorated Stink Bug
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85
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151 # insect phenology model.
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111
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152 threshold = 14.17;
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131
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153 if (is.null(temperature_data_frame)) {
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154 # The values of tmin and tmax cannot be NULL.
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155 curr_min_temp = tmin;
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156 curr_max_temp = tmax;
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157 } else {
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158 # Minimum temperature for current row.
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159 curr_min_temp = temperature_data_frame$TMIN[row];
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160 # Maximum temperature for current row.
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161 curr_max_temp = temperature_data_frame$TMAX[row];
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162 }
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85
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163 # Mean temperature for current row.
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111
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164 curr_mean_temp = 0.5 * (curr_min_temp + curr_max_temp);
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85
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165 # Initialize degree day accumulation
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111
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166 averages = 0;
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102
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167 if (curr_max_temp < threshold) {
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168 averages = 0;
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85
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169 }
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170 else {
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171 # Initialize hourly temperature.
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172 T = NULL;
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85
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173 # Initialize degree hour vector.
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111
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174 dh = NULL;
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131
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175 if (is.null(temperature_data_frame)) {
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176 # The value of daylen cannot be NULL.
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177 y = daylen;
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178 } else {
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179 # Daylight length for current row.
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180 y = temperature_data_frame$DAYLEN[row];
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181 }
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182 # Darkness length.
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111
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183 z = 24 - y;
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85
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184 # Lag coefficient.
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111
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185 a = 1.86;
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85
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186 # Darkness coefficient.
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111
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187 b = 2.20;
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85
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188 # Sunrise time.
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111
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189 risetime = 12 - y / 2;
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85
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190 # Sunset time.
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111
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191 settime = 12 + y / 2;
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192 ts = (curr_max_temp - curr_min_temp) * sin(pi * (settime - 5) / (y + 2 * a)) + curr_min_temp;
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193 for (i in 1:24) {
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194 if (i > risetime && i < settime) {
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195 # Number of hours after Tmin until sunset.
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111
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196 m = i - 5;
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197 T[i] = (curr_max_temp - curr_min_temp) * sin(pi * m / (y + 2 * a)) + curr_min_temp;
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198 if (T[i] < 8.4) {
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199 dh[i] = 0;
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200 }
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201 else {
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202 dh[i] = T[i] - 8.4;
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203 }
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204 }
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96
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205 else if (i > settime) {
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111
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206 n = i - settime;
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207 T[i] = curr_min_temp + (ts - curr_min_temp) * exp( - b * n / z);
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208 if (T[i] < 8.4) {
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209 dh[i] = 0;
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210 }
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211 else {
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212 dh[i] = T[i] - 8.4;
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213 }
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214 }
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215 else {
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111
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216 n = i + 24 - settime;
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217 T[i] = curr_min_temp + (ts - curr_min_temp) * exp( - b * n / z);
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218 if (T[i] < 8.4) {
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219 dh[i] = 0;
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220 }
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221 else {
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222 dh[i] = T[i] - 8.4;
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85
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223 }
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224 }
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225 }
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111
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226 averages = sum(dh) / 24;
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227 }
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103
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228 return(c(curr_mean_temp, averages))
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85
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229 }
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230
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231 is_leap_year = function(date_str) {
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232 # Extract the year from the date_str.
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233 date = format(date_str);
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234 items = strsplit(date, "-")[[1]];
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235 year = as.integer(items[1]);
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236 if (((year %% 4 == 0) & (year %% 100 != 0)) | (year %% 400 == 0)) {
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237 return(TRUE);
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238 } else {
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239 return(FALSE);
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240 }
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241 }
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242
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102
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243 mortality.adult = function(temperature) {
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244 if (temperature < 12.7) {
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111
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245 mortality.probability = 0.002;
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102
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246 }
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247 else {
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111
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248 mortality.probability = temperature * 0.0005 + 0.02;
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102
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249 }
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250 return(mortality.probability)
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85
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251 }
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252
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135
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253 mortality.egg = function(temperature, adj=0) {
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254 # If no input from adjustment, default
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255 # value is 0 (data from Nielsen, 2008).
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256 T.mortality = c(15, 17, 20, 25, 27, 30, 33, 35);
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257 egg.mortality = c(50, 2, 1, 0, 0, 0, 5, 100);
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258 # Calculates slopes and intercepts for lines.
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259 slopes = NULL;
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260 intercepts = NULL;
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261 for (i in 1:length(T.mortality)) {
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262 slopes[i] = (egg.mortality[i+1] - egg.mortality[i]) / (T.mortality[i+1] - T.mortality[i]);
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263 intercepts[i] = -slopes[i] * T.mortality[i] + egg.mortality[i];
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85
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264 }
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135
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265 # Calculates mortality based on temperature.
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266 mortality.probability = NULL;
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267 for (j in 1:length(temperature)) {
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268 mortality.probability[j] = if(temperature[j] <= T.mortality[2]) {
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269 temperature[j] * slopes[1] + intercepts[1];
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270 } else if (temperature[j] > T.mortality[2] && temperature[j] <= T.mortality[3]) {
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271 temperature[j] * slopes[2] + intercepts[2];
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272 } else if (temperature[j] > T.mortality[3] && temperature[j] <= T.mortality[4]) {
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273 temperature[j] * slopes[3] + intercepts[3];
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274 } else if (temperature[j] > T.mortality[4] && temperature[j] <= T.mortality[5]) {
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275 temperature[j] * slopes[4] + intercepts[4];
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276 } else if (temperature[j] > T.mortality[5] && temperature[j] <= T.mortality[6]) {
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277 temperature[j] * slopes[5] + intercepts[5];
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278 } else if (temperature[j] > T.mortality[6] && temperature[j] <= T.mortality[7]) {
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279 temperature[j] * slopes[6] + intercepts[6];
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280 } else if (temperature[j] > T.mortality[7]) {
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281 temperature[j] * slopes[7] + intercepts[7];
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282 }
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283 # If mortality > 100, make it equal to 100.
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284 mortality.probability[mortality.probability>100] = 100;
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285 # If mortality <0, make equal to 0.
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286 mortality.probability[mortality.probability<0] = 0;
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85
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287 }
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135
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288 # Make mortality adjustments based on adj parameter.
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289 mortality.probability = (100 - mortality.probability) * adj + mortality.probability;
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290 # if mortality > 100, make it equal to 100.
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291 mortality.probability[mortality.probability>100] = 100;
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292 # If mortality <0, make equal to 0.
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293 mortality.probability[mortality.probability<0] = 0;
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294 # Change percent to proportion.
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295 mortality.probability = mortality.probability / 100;
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102
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296 return(mortality.probability)
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135
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297 }
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85
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298
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299 mortality.nymph = function(temperature) {
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300 if (temperature < 12.7) {
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111
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301 mortality.probability = 0.03;
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85
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302 }
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303 else {
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111
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304 mortality.probability = temperature * 0.0008 + 0.03;
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85
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305 }
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111
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306 return(mortality.probability);
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102
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307 }
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308
|
|
122
|
309 parse_input_data = function(input_ytd, input_norm, location, start_date, end_date) {
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310 # The end DOY for norm data prepended to ytd data.
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311 prepend_end_doy_norm = 0;
|
|
|
312 # The start DOY for norm data appended to ytd data.
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313 append_start_doy_norm = 0;
|
|
125
|
314 if (is.null(start_date) && is.null(end_date)) {
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|
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315 # We're not dealing with a date interval.
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316 date_interval = FALSE;
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|
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317 if (is.null(input_ytd)) {
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318 # Base all dates on the current date since 30 year
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319 # normals data does not include any dates.
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320 year = format(Sys.Date(), "%Y");
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321 }
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|
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322 } else {
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323 date_interval = TRUE;
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324 year = get_year_from_date(start_date);
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325 # Get the DOY for start_date and end_date.
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326 start_date_doy = as.integer(strftime(start_date, format="%j"));
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327 end_date_doy = as.integer(strftime(end_date, format="%j"));
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328 }
|
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112
|
329 if (is.null(input_ytd)) {
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122
|
330 # We're processing only the 30 year normals data.
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331 processing_year_to_date_data = FALSE;
|
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125
|
332 if (is.null(start_date) && is.null(end_date)) {
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333 # We're processing the entire year, so we can
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334 # set the start_date to Jan 1.
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335 start_date = paste(year, "01", "01", sep="-");
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336 }
|
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122
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337 } else {
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338 processing_year_to_date_data = TRUE;
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125
|
339 # Read the input_ytd temperature data file into a data frame.
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340 temperature_data_frame = get_new_temperature_data_frame(input_ytd=input_ytd);
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341 num_ytd_rows = dim(temperature_data_frame)[1];
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342 if (!date_interval) {
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343 start_date = temperature_data_frame$DATE[1];
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344 year = get_year_from_date(start_date);
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345 }
|
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122
|
346 }
|
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125
|
347 # See if we're in a leap year.
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348 is_leap_year = is_leap_year(start_date);
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122
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349 # Read the input_norm temperature datafile into a data frame.
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125
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350 norm_data_frame = get_new_norm_data_frame(is_leap_year, input_norm=input_norm);
|
|
122
|
351 if (processing_year_to_date_data) {
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|
123
|
352 if (date_interval) {
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122
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353 # We're plotting a date interval.
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354 start_date_ytd_row = which(temperature_data_frame$DATE==start_date);
|
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125
|
355 if (length(start_date_ytd_row) > 0) {
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122
|
356 # The start date is contained within the input_ytd data.
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125
|
357 start_date_ytd_row = start_date_ytd_row[1];
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122
|
358 start_doy_ytd = as.integer(temperature_data_frame$DOY[start_date_ytd_row]);
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|
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359 } else {
|
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360 # The start date is contained within the input_norm data.
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125
|
361 start_date_ytd_row = 0;
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|
362 start_date_norm_row = which(norm_data_frame$DOY==start_date_doy);
|
|
122
|
363 }
|
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|
364 end_date_ytd_row = which(temperature_data_frame$DATE==end_date);
|
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125
|
365 if (length(end_date_ytd_row) > 0) {
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366 end_date_ytd_row = end_date_ytd_row[1];
|
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122
|
367 # The end date is contained within the input_ytd data.
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368 end_doy_ytd = as.integer(temperature_data_frame$DOY[end_date_ytd_row]);
|
|
128
|
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.
|
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372 days_missing = end_doy_ytd - end_date_ytd_row;
|
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373 msg = cat("The year-to-date dataset is missing ", days_missing, " days of data.\n");
|
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|
374 stop_err(msg);
|
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|
375 }
|
|
125
|
376 } else {
|
|
|
377 end_date_ytd_row = 0;
|
|
122
|
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;
|
|
123
|
383 # Temporarily set start_date to get the year.
|
|
122
|
384 start_date = temperature_data_frame$DATE[1];
|
|
125
|
385 end_date_ytd_row = num_ytd_rows;
|
|
|
386 end_date = temperature_data_frame$DATE[num_ytd_rows];
|
|
122
|
387 date_str = format(start_date);
|
|
123
|
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="-");
|
|
122
|
396 # Save the first DOY to later check if start_date is Jan 1.
|
|
|
397 start_doy_ytd = as.integer(temperature_data_frame$DOY[1]);
|
|
125
|
398 end_doy_ytd = as.integer(temperature_data_frame$DOY[num_ytd_rows]);
|
|
128
|
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 }
|
|
122
|
406 }
|
|
|
407 } else {
|
|
|
408 # We're processing only the 30 year normals data, so create an empty
|
|
112
|
409 # data frame for containing temperature data after it is converted
|
|
|
410 # from the 30 year normals format to the year-to-date format.
|
|
125
|
411 temperature_data_frame = get_new_temperature_data_frame();
|
|
123
|
412 if (date_interval) {
|
|
122
|
413 # We're plotting a date interval.
|
|
|
414 # Extract the year, month and day from the start date.
|
|
117
|
415 start_date_str = format(start_date);
|
|
|
416 start_date_str_items = strsplit(start_date_str, "-")[[1]];
|
|
122
|
417 year = start_date_str_items[1];
|
|
117
|
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];
|
|
123
|
426 end_date = paste(year, end_date_month, end_date_day, sep="-");
|
|
122
|
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="-");
|
|
117
|
431 }
|
|
112
|
432 }
|
|
122
|
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) {
|
|
112
|
435 location = norm_data_frame$NAME[1];
|
|
|
436 }
|
|
122
|
437 if (processing_year_to_date_data) {
|
|
|
438 # Merge the year-to-date data with the 30 year normals data.
|
|
123
|
439 if (date_interval) {
|
|
122
|
440 # The values of start_date_ytd_row and end_date_ytd_row were set above.
|
|
|
441 if (start_date_ytd_row > 0 & end_date_ytd_row > 0) {
|
|
|
442 # The date interval is contained within the input_ytd
|
|
|
443 # data, so we don't need to merge the 30 year normals data.
|
|
|
444 temperature_data_frame = temperature_data_frame[start_date_ytd_row:end_date_ytd_row,];
|
|
|
445 } else if (start_date_ytd_row == 0 & end_date_ytd_row > 0) {
|
|
|
446 # The date interval starts in input_norm and ends in
|
|
|
447 # input_ytd, so prepend appropriate rows from input_norm
|
|
|
448 # to appropriate rows from input_ytd.
|
|
|
449 first_norm_row = which(norm_data_frame$DOY==start_date_doy);
|
|
|
450 # Get the first DOY from temperature_data_frame.
|
|
|
451 first_ytd_doy = temperature_data_frame$DOY[1];
|
|
|
452 # End DOY of input_norm data prepended to input_ytd.
|
|
|
453 prepend_end_doy_norm = first_ytd_doy - 1;
|
|
|
454 # Get the number of rows for the restricted date interval
|
|
|
455 # that are contained in temperature_data_frame.
|
|
125
|
456 num_temperature_data_frame_rows = end_date_ytd_row;
|
|
122
|
457 # Get the last row needed from the 30 year normals data.
|
|
|
458 last_norm_row = which(norm_data_frame$DOY==prepend_end_doy_norm);
|
|
|
459 # Get the number of rows for the restricted date interval
|
|
|
460 # that are contained in norm_data_frame.
|
|
125
|
461 num_norm_data_frame_rows = last_norm_row - first_norm_row;
|
|
122
|
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.
|
|
125
|
465 tmp_norm_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
|
|
|
466 j = 1;
|
|
122
|
467 for (i in first_norm_row:last_norm_row) {
|
|
|
468 # Populate the temp_data_frame row with
|
|
|
469 # values from norm_data_frame.
|
|
125
|
470 tmp_norm_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
|
|
|
471 j = j + 1;
|
|
122
|
472 }
|
|
|
473 # Create a second temporary data frame containing the
|
|
|
474 # appropriate rows from temperature_data_frame.
|
|
125
|
475 tmp_temperature_data_frame = temperature_data_frame[1:num_temperature_data_frame_rows,];
|
|
122
|
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
|
|
125
|
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;
|
|
122
|
484 # Get the DOY of the last row in the input_ytd data.
|
|
125
|
485 last_ytd_doy = temperature_data_frame$DOY[num_ytd_rows];
|
|
122
|
486 # Get the DOYs for the first and last rows from norm_data_frame
|
|
|
487 # that will be appended to temperature_data_frame.
|
|
|
488 append_start_doy_norm = last_ytd_doy + 1;
|
|
|
489 # Get the row from norm_data_frame containing first_norm_doy.
|
|
|
490 first_norm_row = which(norm_data_frame$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$DOY == end_date_doy);
|
|
|
493 # Get the number of rows for the restricted date interval
|
|
|
494 # that are contained in norm_data_frame.
|
|
125
|
495 num_norm_data_frame_rows = last_norm_row - first_norm_row;
|
|
122
|
496 # Create a temporary data frame to contain the data
|
|
125
|
497 # taken from both temperature_data_frame and norm_data_frame
|
|
122
|
498 # for the date interval.
|
|
125
|
499 tmp_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
|
|
122
|
500 # Populate tmp_data_frame with the appropriate rows from temperature_data_frame.
|
|
125
|
501 j = start_date_ytd_row;
|
|
|
502 for (i in 1:num_temperature_data_frame_rows) {
|
|
|
503 tmp_data_frame[i,] = temperature_data_frame[j,];
|
|
|
504 j = j + 1;
|
|
|
505 }
|
|
122
|
506 # Apppend the appropriate rows from norm_data_frame to tmp_data_frame.
|
|
125
|
507 current_iteration = num_temperature_data_frame_rows + 1;
|
|
|
508 num_iterations = current_iteration + num_norm_data_frame_rows;
|
|
|
509 j = first_norm_row;
|
|
|
510 for (i in current_iteration:num_iterations) {
|
|
|
511 tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, j);
|
|
|
512 j = j + 1;
|
|
122
|
513 }
|
|
|
514 temperature_data_frame = tmp_data_frame[,];
|
|
|
515 } else if (start_date_ytd_row == 0 & end_date_ytd_row == 0) {
|
|
|
516 # The date interval is contained witin input_norm.
|
|
125
|
517 temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
|
|
122
|
518 }
|
|
|
519 } else {
|
|
|
520 # We're plotting an entire year.
|
|
|
521 if (start_doy_ytd > 1) {
|
|
|
522 # The input_ytd data starts after Jan 1, so prepend
|
|
|
523 # appropriate rows from input_norm to temperature_data_frame.
|
|
|
524 prepend_end_doy_norm = start_doy_ytd - 1;
|
|
|
525 last_norm_row = which(norm_data_frame$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.
|
|
124
|
530 for (i in 1:last_norm_row) {
|
|
|
531 tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
|
|
122
|
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$DOY == append_start_doy_norm);
|
|
|
542 # Append the 30 year normals data to the year-to-date data.
|
|
123
|
543 for (i in first_norm_row:total_days) {
|
|
124
|
544 temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
|
|
122
|
545 }
|
|
|
546 }
|
|
112
|
547 }
|
|
|
548 } else {
|
|
122
|
549 # We're processing only the 30 year normals data.
|
|
123
|
550 if (date_interval) {
|
|
122
|
551 # Populate temperature_data_frame from norm_data_frame.
|
|
125
|
552 temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
|
|
122
|
553 } else {
|
|
|
554 total_days = get_total_days(is_leap_year);
|
|
|
555 for (i in 1:total_days) {
|
|
124
|
556 temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
|
|
112
|
557 }
|
|
|
558 }
|
|
|
559 }
|
|
|
560 # Add a column containing the daylight length for each day.
|
|
122
|
561 temperature_data_frame = add_daylight_length(temperature_data_frame);
|
|
|
562 return(list(temperature_data_frame, start_date, end_date, prepend_end_doy_norm, append_start_doy_norm, is_leap_year, location));
|
|
85
|
563 }
|
|
|
564
|
|
125
|
565 # Import the shared utility functions.
|
|
|
566 utils_path <- paste(opt$script_dir, "utils.R", sep="/");
|
|
|
567 source(utils_path);
|
|
117
|
568
|
|
123
|
569 if (is.null(opt$input_ytd)) {
|
|
122
|
570 processing_year_to_date_data = FALSE;
|
|
|
571 } else {
|
|
|
572 processing_year_to_date_data = TRUE;
|
|
|
573 }
|
|
112
|
574 # Determine if we're plotting generations separately.
|
|
|
575 if (opt$plot_generations_separately=="yes") {
|
|
|
576 plot_generations_separately = TRUE;
|
|
|
577 } else {
|
|
|
578 plot_generations_separately = FALSE;
|
|
|
579 }
|
|
124
|
580 # Parse the inputs.
|
|
|
581 data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$location, opt$start_date, opt$end_date);
|
|
|
582 temperature_data_frame = data_list[[1]];
|
|
|
583 # Information needed for plots, some of these values are
|
|
|
584 # being reset here since in some case they were set above.
|
|
|
585 start_date = data_list[[2]];
|
|
|
586 end_date = data_list[[3]];
|
|
|
587 prepend_end_doy_norm = data_list[[4]];
|
|
|
588 append_start_doy_norm = data_list[[5]];
|
|
|
589 is_leap_year = data_list[[6]];
|
|
|
590 location = data_list[[7]];
|
|
|
591
|
|
125
|
592 # We're plotting an entire year.
|
|
|
593 # Display the total number of days in the Galaxy history item blurb.
|
|
|
594 if (processing_year_to_date_data) {
|
|
|
595 cat("Number of days year-to-date: ", opt$num_days_ytd, "\n");
|
|
117
|
596 } else {
|
|
125
|
597 if (is_leap_year) {
|
|
|
598 num_days = 366;
|
|
|
599 } else {
|
|
|
600 num_days = 365;
|
|
117
|
601 }
|
|
125
|
602 cat("Number of days in year: ", num_days, "\n");
|
|
117
|
603 }
|
|
125
|
604
|
|
112
|
605 # All latitude values are the same, so get the value for plots from the first row.
|
|
111
|
606 latitude = temperature_data_frame$LATITUDE[1];
|
|
112
|
607
|
|
|
608 # Determine the specified life stages for processing.
|
|
|
609 # Split life_stages into a list of strings for plots.
|
|
|
610 life_stages_str = as.character(opt$life_stages);
|
|
|
611 life_stages = strsplit(life_stages_str, ",")[[1]];
|
|
85
|
612
|
|
112
|
613 # Determine the data we need to generate for plotting.
|
|
|
614 process_eggs = FALSE;
|
|
|
615 process_nymphs = FALSE;
|
|
|
616 process_young_nymphs = FALSE;
|
|
|
617 process_old_nymphs = FALSE;
|
|
|
618 process_total_nymphs = FALSE;
|
|
|
619 process_adults = FALSE;
|
|
|
620 process_previttelogenic_adults = FALSE;
|
|
|
621 process_vittelogenic_adults = FALSE;
|
|
|
622 process_diapausing_adults = FALSE;
|
|
|
623 process_total_adults = FALSE;
|
|
126
|
624 process_total = FALSE;
|
|
112
|
625 for (life_stage in life_stages) {
|
|
|
626 if (life_stage=="Total") {
|
|
|
627 process_eggs = TRUE;
|
|
|
628 process_nymphs = TRUE;
|
|
|
629 process_adults = TRUE;
|
|
126
|
630 process_total = TRUE;
|
|
112
|
631 } else if (life_stage=="Egg") {
|
|
|
632 process_eggs = TRUE;
|
|
|
633 } else if (life_stage=="Nymph") {
|
|
|
634 process_nymphs = TRUE;
|
|
|
635 } else if (life_stage=="Adult") {
|
|
|
636 process_adults = TRUE;
|
|
|
637 }
|
|
|
638 }
|
|
|
639 if (process_nymphs) {
|
|
|
640 # Split life_stages_nymph into a list of strings for plots.
|
|
|
641 life_stages_nymph_str = as.character(opt$life_stages_nymph);
|
|
|
642 life_stages_nymph = strsplit(life_stages_nymph_str, ",")[[1]];
|
|
|
643 for (life_stage_nymph in life_stages_nymph) {
|
|
|
644 if (life_stage_nymph=="Young") {
|
|
|
645 process_young_nymphs = TRUE;
|
|
|
646 } else if (life_stage_nymph=="Old") {
|
|
|
647 process_old_nymphs = TRUE;
|
|
|
648 } else if (life_stage_nymph=="Total") {
|
|
|
649 process_total_nymphs = TRUE;
|
|
|
650 }
|
|
|
651 }
|
|
|
652 }
|
|
|
653 if (process_adults) {
|
|
|
654 # Split life_stages_adult into a list of strings for plots.
|
|
|
655 life_stages_adult_str = as.character(opt$life_stages_adult);
|
|
|
656 life_stages_adult = strsplit(life_stages_adult_str, ",")[[1]];
|
|
|
657 for (life_stage_adult in life_stages_adult) {
|
|
|
658 if (life_stage_adult=="Pre-vittelogenic") {
|
|
|
659 process_previttelogenic_adults = TRUE;
|
|
|
660 } else if (life_stage_adult=="Vittelogenic") {
|
|
|
661 process_vittelogenic_adults = TRUE;
|
|
|
662 } else if (life_stage_adult=="Diapausing") {
|
|
|
663 process_diapausing_adults = TRUE;
|
|
|
664 } else if (life_stage_adult=="Total") {
|
|
|
665 process_total_adults = TRUE;
|
|
|
666 }
|
|
|
667 }
|
|
|
668 }
|
|
97
|
669 # Initialize matrices.
|
|
122
|
670 total_days = dim(temperature_data_frame)[1];
|
|
112
|
671 if (process_eggs) {
|
|
|
672 Eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
673 }
|
|
|
674 if (process_young_nymphs | process_total_nymphs) {
|
|
|
675 YoungNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
676 }
|
|
|
677 if (process_old_nymphs | process_total_nymphs) {
|
|
|
678 OldNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
679 }
|
|
|
680 if (process_previttelogenic_adults | process_total_adults) {
|
|
|
681 Previttelogenic.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
682 }
|
|
|
683 if (process_vittelogenic_adults | process_total_adults) {
|
|
|
684 Vittelogenic.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
685 }
|
|
|
686 if (process_diapausing_adults | process_total_adults) {
|
|
|
687 Diapausing.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
688 }
|
|
|
689 newborn.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
690 adult.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
691 death.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
692 if (plot_generations_separately) {
|
|
|
693 # P is Parental, or overwintered adults.
|
|
|
694 P.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
695 # F1 is the first field-produced generation.
|
|
|
696 F1.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
697 # F2 is the second field-produced generation.
|
|
|
698 F2.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
699 if (process_eggs) {
|
|
|
700 P_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
701 F1_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
702 F2_eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
703 }
|
|
|
704 if (process_young_nymphs) {
|
|
|
705 P_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
706 F1_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
707 F2_young_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
708 }
|
|
|
709 if (process_old_nymphs) {
|
|
|
710 P_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
711 F1_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
712 F2_old_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
713 }
|
|
|
714 if (process_total_nymphs) {
|
|
|
715 P_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
716 F1_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
717 F2_total_nymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
718 }
|
|
|
719 if (process_previttelogenic_adults) {
|
|
|
720 P_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
721 F1_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
722 F2_previttelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
723 }
|
|
|
724 if (process_vittelogenic_adults) {
|
|
|
725 P_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
726 F1_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
727 F2_vittelogenic_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
728 }
|
|
|
729 if (process_diapausing_adults) {
|
|
|
730 P_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
731 F1_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
732 F2_diapausing_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
733 }
|
|
|
734 if (process_total_adults) {
|
|
|
735 P_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
736 F1_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
737 F2_total_adults.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
|
738 }
|
|
|
739 }
|
|
|
740 # Total population.
|
|
|
741 population.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
|
|
103
|
742
|
|
135
|
743 doy_zero_insects = NULL;
|
|
102
|
744 # Process replications.
|
|
112
|
745 for (current_replication in 1:opt$replications) {
|
|
109
|
746 # Start with the user-defined number of insects per replication.
|
|
111
|
747 num_insects = opt$insects_per_replication;
|
|
90
|
748 # Generation, Stage, degree-days, T, Diapause.
|
|
111
|
749 vector.ini = c(0, 3, 0, 0, 0);
|
|
112
|
750 # Replicate to create a matrix where the columns are
|
|
|
751 # Generation, Stage, degree-days, T, Diapause and the
|
|
|
752 # rows are the initial number of insects per replication.
|
|
111
|
753 vector.matrix = rep(vector.ini, num_insects);
|
|
112
|
754 # Complete transposed matrix for the population, so now
|
|
|
755 # the rows are Generation, Stage, degree-days, T, Diapause
|
|
111
|
756 vector.matrix = base::t(matrix(vector.matrix, nrow=5));
|
|
85
|
757 # Time series of population size.
|
|
112
|
758 if (process_eggs) {
|
|
|
759 Eggs = rep(0, total_days);
|
|
|
760 }
|
|
|
761 if (process_young_nymphs | process_total_nymphs) {
|
|
|
762 YoungNymphs = rep(0, total_days);
|
|
|
763 }
|
|
|
764 if (process_old_nymphs | process_total_nymphs) {
|
|
|
765 OldNymphs = rep(0, total_days);
|
|
|
766 }
|
|
|
767 if (process_previttelogenic_adults | process_total_adults) {
|
|
|
768 Previttelogenic = rep(0, total_days);
|
|
|
769 }
|
|
|
770 if (process_vittelogenic_adults | process_total_adults) {
|
|
|
771 Vittelogenic = rep(0, total_days);
|
|
|
772 }
|
|
|
773 if (process_diapausing_adults | process_total_adults) {
|
|
|
774 Diapausing = rep(0, total_days);
|
|
|
775 }
|
|
|
776 N.newborn = rep(0, total_days);
|
|
|
777 N.adult = rep(0, total_days);
|
|
|
778 N.death = rep(0, total_days);
|
|
|
779 overwintering_adult.population = rep(0, total_days);
|
|
|
780 first_generation.population = rep(0, total_days);
|
|
|
781 second_generation.population = rep(0, total_days);
|
|
|
782 if (plot_generations_separately) {
|
|
|
783 # P is Parental, or overwintered adults.
|
|
|
784 # F1 is the first field-produced generation.
|
|
|
785 # F2 is the second field-produced generation.
|
|
|
786 if (process_eggs) {
|
|
|
787 P.egg = rep(0, total_days);
|
|
|
788 F1.egg = rep(0, total_days);
|
|
|
789 F2.egg = rep(0, total_days);
|
|
|
790 }
|
|
|
791 if (process_young_nymphs) {
|
|
|
792 P.young_nymph = rep(0, total_days);
|
|
|
793 F1.young_nymph = rep(0, total_days);
|
|
|
794 F2.young_nymph = rep(0, total_days);
|
|
|
795 }
|
|
|
796 if (process_old_nymphs) {
|
|
|
797 P.old_nymph = rep(0, total_days);
|
|
|
798 F1.old_nymph = rep(0, total_days);
|
|
|
799 F2.old_nymph = rep(0, total_days);
|
|
|
800 }
|
|
|
801 if (process_total_nymphs) {
|
|
|
802 P.total_nymph = rep(0, total_days);
|
|
|
803 F1.total_nymph = rep(0, total_days);
|
|
|
804 F2.total_nymph = rep(0, total_days);
|
|
|
805 }
|
|
|
806 if (process_previttelogenic_adults) {
|
|
|
807 P.previttelogenic_adult = rep(0, total_days);
|
|
|
808 F1.previttelogenic_adult = rep(0, total_days);
|
|
|
809 F2.previttelogenic_adult = rep(0, total_days);
|
|
|
810 }
|
|
|
811 if (process_vittelogenic_adults) {
|
|
|
812 P.vittelogenic_adult = rep(0, total_days);
|
|
|
813 F1.vittelogenic_adult = rep(0, total_days);
|
|
|
814 F2.vittelogenic_adult = rep(0, total_days);
|
|
|
815 }
|
|
|
816 if (process_diapausing_adults) {
|
|
|
817 P.diapausing_adult = rep(0, total_days);
|
|
|
818 F1.diapausing_adult = rep(0, total_days);
|
|
|
819 F2.diapausing_adult = rep(0, total_days);
|
|
|
820 }
|
|
|
821 if (process_total_adults) {
|
|
|
822 P.total_adult = rep(0, total_days);
|
|
|
823 F1.total_adult = rep(0, total_days);
|
|
|
824 F2.total_adult = rep(0, total_days);
|
|
|
825 }
|
|
|
826 }
|
|
111
|
827 total.population = NULL;
|
|
112
|
828 averages.day = rep(0, total_days);
|
|
|
829 # All the days included in the input_ytd temperature dataset.
|
|
|
830 for (row in 1:total_days) {
|
|
85
|
831 # Get the integer day of the year for the current row.
|
|
111
|
832 doy = temperature_data_frame$DOY[row];
|
|
85
|
833 # Photoperiod in the day.
|
|
111
|
834 photoperiod = temperature_data_frame$DAYLEN[row];
|
|
131
|
835 temp.profile = get_temperature_at_hour(latitude, row, temperature_data_frame=temperature_data_frame);
|
|
111
|
836 mean.temp = temp.profile[1];
|
|
|
837 averages.temp = temp.profile[2];
|
|
|
838 averages.day[row] = averages.temp;
|
|
85
|
839 # Trash bin for death.
|
|
111
|
840 death.vector = NULL;
|
|
85
|
841 # Newborn.
|
|
111
|
842 birth.vector = NULL;
|
|
85
|
843 # All individuals.
|
|
135
|
844 if (num_insects > 0) {
|
|
|
845 for (i in 1:num_insects) {
|
|
|
846 # Individual record.
|
|
|
847 vector.individual = vector.matrix[i,];
|
|
|
848 # Adjustment for late season mortality rate (still alive?).
|
|
|
849 if (latitude < 40.0) {
|
|
|
850 post.mortality = 1;
|
|
|
851 day.kill = 300;
|
|
|
852 }
|
|
|
853 else {
|
|
|
854 post.mortality = 2;
|
|
|
855 day.kill = 250;
|
|
|
856 }
|
|
|
857 if (vector.individual[2] == 0) {
|
|
|
858 # Egg.
|
|
|
859 death.probability = opt$egg_mortality * mortality.egg(mean.temp, adj=opt$egg_mortality);
|
|
|
860 }
|
|
|
861 else if (vector.individual[2] == 1 | vector.individual[2] == 2) {
|
|
|
862 # Nymph.
|
|
|
863 death.probability = opt$nymph_mortality * mortality.nymph(mean.temp);
|
|
|
864 }
|
|
|
865 else if (vector.individual[2] == 3 | vector.individual[2] == 4 | vector.individual[2] == 5) {
|
|
|
866 # Adult.
|
|
|
867 if (doy < day.kill) {
|
|
|
868 death.probability = opt$adult_mortality * mortality.adult(mean.temp);
|
|
|
869 }
|
|
|
870 else {
|
|
|
871 # Increase adult mortality after fall equinox.
|
|
|
872 death.probability = opt$adult_mortality * post.mortality * mortality.adult(mean.temp);
|
|
|
873 }
|
|
|
874 }
|
|
|
875 # Dependent on temperature and life stage?
|
|
|
876 u.d = runif(1);
|
|
|
877 if (u.d < death.probability) {
|
|
|
878 death.vector = c(death.vector, i);
|
|
85
|
879 }
|
|
|
880 else {
|
|
135
|
881 # End of diapause.
|
|
|
882 if (vector.individual[1] == 0 && vector.individual[2] == 3) {
|
|
|
883 # Overwintering adult (pre-vittelogenic).
|
|
|
884 if (photoperiod > opt$photoperiod && vector.individual[3] > 68 && doy < 180) {
|
|
|
885 # Add 68C to become fully reproductively matured.
|
|
|
886 # Transfer to vittelogenic.
|
|
|
887 vector.individual = c(0, 4, 0, 0, 0);
|
|
|
888 vector.matrix[i,] = vector.individual;
|
|
|
889 }
|
|
|
890 else {
|
|
|
891 # Add average temperature for current day.
|
|
|
892 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
893 # Add 1 day in current stage.
|
|
|
894 vector.individual[4] = vector.individual[4] + 1;
|
|
|
895 vector.matrix[i,] = vector.individual;
|
|
|
896 }
|
|
85
|
897 }
|
|
135
|
898 if (vector.individual[1] != 0 && vector.individual[2] == 3) {
|
|
|
899 # Not overwintering adult (pre-vittelogenic).
|
|
|
900 current.gen = vector.individual[1];
|
|
|
901 if (vector.individual[3] > 68) {
|
|
|
902 # Add 68C to become fully reproductively matured.
|
|
|
903 # Transfer to vittelogenic.
|
|
|
904 vector.individual = c(current.gen, 4, 0, 0, 0);
|
|
|
905 vector.matrix[i,] = vector.individual;
|
|
|
906 }
|
|
|
907 else {
|
|
|
908 # Add average temperature for current day.
|
|
|
909 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
910 # Add 1 day in current stage.
|
|
|
911 vector.individual[4] = vector.individual[4] + 1;
|
|
|
912 vector.matrix[i,] = vector.individual;
|
|
|
913 }
|
|
85
|
914 }
|
|
135
|
915 # Oviposition -- where population dynamics comes from.
|
|
|
916 if (vector.individual[2] == 4 && vector.individual[1] == 0 && mean.temp > 10) {
|
|
|
917 # Vittelogenic stage, overwintering generation.
|
|
|
918 if (vector.individual[4] == 0) {
|
|
|
919 # Just turned in vittelogenic stage.
|
|
|
920 num_insects.birth = round(runif(1, 2 + opt$min_clutch_size, 8 + opt$max_clutch_size));
|
|
|
921 }
|
|
|
922 else {
|
|
|
923 # Daily probability of birth.
|
|
|
924 p.birth = opt$oviposition * 0.01;
|
|
|
925 u1 = runif(1);
|
|
|
926 if (u1 < p.birth) {
|
|
|
927 num_insects.birth = round(runif(1, 2, 8));
|
|
|
928 }
|
|
|
929 }
|
|
103
|
930 # Add average temperature for current day.
|
|
111
|
931 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
85
|
932 # Add 1 day in current stage.
|
|
111
|
933 vector.individual[4] = vector.individual[4] + 1;
|
|
|
934 vector.matrix[i,] = vector.individual;
|
|
135
|
935 if (num_insects.birth > 0) {
|
|
|
936 # Add new birth -- might be in different generations.
|
|
|
937 new.gen = vector.individual[1] + 1;
|
|
|
938 # Egg profile.
|
|
|
939 new.individual = c(new.gen, 0, 0, 0, 0);
|
|
|
940 new.vector = rep(new.individual, num_insects.birth);
|
|
|
941 # Update batch of egg profile.
|
|
|
942 new.vector = t(matrix(new.vector, nrow=5));
|
|
|
943 # Group with total eggs laid in that day.
|
|
|
944 birth.vector = rbind(birth.vector, new.vector);
|
|
85
|
945 }
|
|
|
946 }
|
|
135
|
947 # Oviposition -- for generation 1.
|
|
|
948 if (vector.individual[2] == 4 && vector.individual[1] == 1 && mean.temp > 12.5 && doy < 222) {
|
|
|
949 # Vittelogenic stage, 1st generation
|
|
|
950 if (vector.individual[4] == 0) {
|
|
|
951 # Just turned in vittelogenic stage.
|
|
|
952 num_insects.birth = round(runif(1, 2+opt$min_clutch_size, 8+opt$max_clutch_size));
|
|
|
953 }
|
|
|
954 else {
|
|
|
955 # Daily probability of birth.
|
|
|
956 p.birth = opt$oviposition * 0.01;
|
|
|
957 u1 = runif(1);
|
|
|
958 if (u1 < p.birth) {
|
|
|
959 num_insects.birth = round(runif(1, 2, 8));
|
|
|
960 }
|
|
|
961 }
|
|
|
962 # Add average temperature for current day.
|
|
|
963 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
964 # Add 1 day in current stage.
|
|
|
965 vector.individual[4] = vector.individual[4] + 1;
|
|
|
966 vector.matrix[i,] = vector.individual;
|
|
|
967 if (num_insects.birth > 0) {
|
|
|
968 # Add new birth -- might be in different generations.
|
|
|
969 new.gen = vector.individual[1] + 1;
|
|
|
970 # Egg profile.
|
|
|
971 new.individual = c(new.gen, 0, 0, 0, 0);
|
|
|
972 new.vector = rep(new.individual, num_insects.birth);
|
|
|
973 # Update batch of egg profile.
|
|
|
974 new.vector = t(matrix(new.vector, nrow=5));
|
|
|
975 # Group with total eggs laid in that day.
|
|
|
976 birth.vector = rbind(birth.vector, new.vector);
|
|
85
|
977 }
|
|
|
978 }
|
|
135
|
979 # Egg to young nymph.
|
|
|
980 if (vector.individual[2] == 0) {
|
|
|
981 # Add average temperature for current day.
|
|
|
982 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
983 if (vector.individual[3] >= (68+opt$young_nymph_accumulation)) {
|
|
|
984 # From egg to young nymph, degree-days requirement met.
|
|
|
985 current.gen = vector.individual[1];
|
|
|
986 # Transfer to young nymph stage.
|
|
|
987 vector.individual = c(current.gen, 1, 0, 0, 0);
|
|
|
988 }
|
|
|
989 else {
|
|
|
990 # Add 1 day in current stage.
|
|
|
991 vector.individual[4] = vector.individual[4] + 1;
|
|
|
992 }
|
|
|
993 vector.matrix[i,] = vector.individual;
|
|
85
|
994 }
|
|
135
|
995 # Young nymph to old nymph.
|
|
|
996 if (vector.individual[2] == 1) {
|
|
|
997 # Add average temperature for current day.
|
|
|
998 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
999 if (vector.individual[3] >= (250+opt$old_nymph_accumulation)) {
|
|
|
1000 # From young to old nymph, degree_days requirement met.
|
|
|
1001 current.gen = vector.individual[1];
|
|
|
1002 # Transfer to old nym stage.
|
|
|
1003 vector.individual = c(current.gen, 2, 0, 0, 0);
|
|
|
1004 if (photoperiod < opt$photoperiod && doy > 180) {
|
|
|
1005 vector.individual[5] = 1;
|
|
|
1006 } # Prepare for diapausing.
|
|
85
|
1007 }
|
|
|
1008 else {
|
|
135
|
1009 # Add 1 day in current stage.
|
|
|
1010 vector.individual[4] = vector.individual[4] + 1;
|
|
85
|
1011 }
|
|
135
|
1012 vector.matrix[i,] = vector.individual;
|
|
85
|
1013 }
|
|
135
|
1014 # Old nymph to adult: pre-vittelogenic or diapausing?
|
|
|
1015 if (vector.individual[2] == 2) {
|
|
|
1016 # Add average temperature for current day.
|
|
|
1017 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
1018 if (vector.individual[3] >= (200+opt$adult_accumulation)) {
|
|
|
1019 # From old to adult, degree_days requirement met.
|
|
|
1020 current.gen = vector.individual[1];
|
|
|
1021 if (vector.individual[5] == 0) {
|
|
|
1022 # Previttelogenic.
|
|
|
1023 vector.individual = c(current.gen, 3, 0, 0, 0);
|
|
|
1024 }
|
|
|
1025 else {
|
|
|
1026 # Diapausing.
|
|
|
1027 vector.individual = c(current.gen, 5, 0, 0, 1);
|
|
|
1028 }
|
|
|
1029 }
|
|
|
1030 else {
|
|
|
1031 # Add 1 day in current stage.
|
|
|
1032 vector.individual[4] = vector.individual[4] + 1;
|
|
|
1033 }
|
|
|
1034 vector.matrix[i,] = vector.individual;
|
|
85
|
1035 }
|
|
135
|
1036 # Growing of diapausing adult (unimportant, but still necessary).
|
|
|
1037 if (vector.individual[2] == 5) {
|
|
|
1038 vector.individual[3] = vector.individual[3] + averages.temp;
|
|
|
1039 vector.individual[4] = vector.individual[4] + 1;
|
|
|
1040 vector.matrix[i,] = vector.individual;
|
|
|
1041 }
|
|
|
1042 } # Else if it is still alive.
|
|
|
1043 } # End of the individual bug loop.
|
|
107
|
1044
|
|
135
|
1045 # Number of deaths.
|
|
|
1046 num_insects.death = length(death.vector);
|
|
|
1047 if (num_insects.death > 0) {
|
|
|
1048 # Remove record of dead.
|
|
|
1049 vector.matrix = vector.matrix[-death.vector,];
|
|
|
1050 }
|
|
|
1051 # Number of births.
|
|
|
1052 num_insects.newborn = length(birth.vector[,1]);
|
|
|
1053 vector.matrix = rbind(vector.matrix, birth.vector);
|
|
|
1054 # Update population size for the next day.
|
|
|
1055 num_insects = num_insects - num_insects.death + num_insects.newborn;
|
|
85
|
1056 }
|
|
135
|
1057 else {
|
|
|
1058 if (is.null(doy_zero_insects) {
|
|
|
1059 # Only set the doy for zero insects if
|
|
|
1060 # it has not yet been set.
|
|
|
1061 doy_zero_insects = doy;
|
|
|
1062 }
|
|
|
1063 }
|
|
85
|
1064
|
|
112
|
1065 # Aggregate results by day. Due to multiple transpose calls
|
|
|
1066 # on vector.matrix above, the columns of vector.matrix
|
|
|
1067 # are now Generation, Stage, degree-days, T, Diapause,
|
|
|
1068 if (process_eggs) {
|
|
|
1069 # For egg population size, column 2 (Stage), must be 0.
|
|
|
1070 Eggs[row] = sum(vector.matrix[,2]==0);
|
|
|
1071 }
|
|
|
1072 if (process_young_nymphs | process_total_nymphs) {
|
|
|
1073 # For young nymph population size, column 2 (Stage) must be 1.
|
|
|
1074 YoungNymphs[row] = sum(vector.matrix[,2]==1);
|
|
|
1075 }
|
|
|
1076 if (process_old_nymphs | process_total_nymphs) {
|
|
|
1077 # For old nymph population size, column 2 (Stage) must be 2.
|
|
|
1078 OldNymphs[row] = sum(vector.matrix[,2]==2);
|
|
|
1079 }
|
|
|
1080 if (process_previttelogenic_adults | process_total_adults) {
|
|
|
1081 # For pre-vittelogenic population size, column 2 (Stage) must be 3.
|
|
|
1082 Previttelogenic[row] = sum(vector.matrix[,2]==3);
|
|
|
1083 }
|
|
|
1084 if (process_vittelogenic_adults | process_total_adults) {
|
|
|
1085 # For vittelogenic population size, column 2 (Stage) must be 4.
|
|
|
1086 Vittelogenic[row] = sum(vector.matrix[,2]==4);
|
|
|
1087 }
|
|
|
1088 if (process_diapausing_adults | process_total_adults) {
|
|
|
1089 # For diapausing population size, column 2 (Stage) must be 5.
|
|
|
1090 Diapausing[row] = sum(vector.matrix[,2]==5);
|
|
|
1091 }
|
|
107
|
1092
|
|
|
1093 # Newborn population size.
|
|
111
|
1094 N.newborn[row] = num_insects.newborn;
|
|
107
|
1095 # Adult population size.
|
|
111
|
1096 N.adult[row] = sum(vector.matrix[,2]==3) + sum(vector.matrix[,2]==4) + sum(vector.matrix[,2]==5);
|
|
107
|
1097 # Dead population size.
|
|
111
|
1098 N.death[row] = num_insects.death;
|
|
107
|
1099
|
|
111
|
1100 total.population = c(total.population, num_insects);
|
|
107
|
1101
|
|
112
|
1102 # For overwintering adult (P) population
|
|
|
1103 # size, column 1 (Generation) must be 0.
|
|
111
|
1104 overwintering_adult.population[row] = sum(vector.matrix[,1]==0);
|
|
112
|
1105 # For first field generation (F1) population
|
|
|
1106 # size, column 1 (Generation) must be 1.
|
|
111
|
1107 first_generation.population[row] = sum(vector.matrix[,1]==1);
|
|
112
|
1108 # For second field generation (F2) population
|
|
|
1109 # size, column 1 (Generation) must be 2.
|
|
111
|
1110 second_generation.population[row] = sum(vector.matrix[,1]==2);
|
|
107
|
1111
|
|
112
|
1112 if (plot_generations_separately) {
|
|
|
1113 if (process_eggs) {
|
|
|
1114 # For egg life stage of generation P population size,
|
|
|
1115 # column 1 (generation) is 0 and column 2 (Stage) is 0.
|
|
|
1116 P.egg[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==0);
|
|
|
1117 # For egg life stage of generation F1 population size,
|
|
|
1118 # column 1 (generation) is 1 and column 2 (Stage) is 0.
|
|
|
1119 F1.egg[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==0);
|
|
|
1120 # For egg life stage of generation F2 population size,
|
|
|
1121 # column 1 (generation) is 2 and column 2 (Stage) is 0.
|
|
|
1122 F2.egg[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==0);
|
|
|
1123 }
|
|
|
1124 if (process_young_nymphs) {
|
|
|
1125 # For young nymph life stage of generation P population
|
|
|
1126 # size, the following combination is required:
|
|
|
1127 # - column 1 (Generation) is 0 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1128 P.young_nymph[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==1);
|
|
|
1129 # For young nymph life stage of generation F1 population
|
|
|
1130 # size, the following combination is required:
|
|
|
1131 # - column 1 (Generation) is 1 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1132 F1.young_nymph[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==1);
|
|
|
1133 # For young nymph life stage of generation F2 population
|
|
|
1134 # size, the following combination is required:
|
|
|
1135 # - column 1 (Generation) is 2 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1136 F2.young_nymph[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==1);
|
|
|
1137 }
|
|
|
1138 if (process_old_nymphs) {
|
|
|
1139 # For old nymph life stage of generation P population
|
|
|
1140 # size, the following combination is required:
|
|
|
1141 # - column 1 (Generation) is 0 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1142 P.old_nymph[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==2);
|
|
|
1143 # For old nymph life stage of generation F1 population
|
|
|
1144 # size, the following combination is required:
|
|
|
1145 # - column 1 (Generation) is 1 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1146 F1.old_nymph[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==2);
|
|
|
1147 # For old nymph life stage of generation F2 population
|
|
|
1148 # size, the following combination is required:
|
|
|
1149 # - column 1 (Generation) is 2 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1150 F2.old_nymph[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==2);
|
|
|
1151 }
|
|
|
1152 if (process_total_nymphs) {
|
|
|
1153 # For total nymph life stage of generation P population
|
|
|
1154 # size, one of the following combinations is required:
|
|
|
1155 # - column 1 (Generation) is 0 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1156 # - column 1 (Generation) is 0 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1157 P.total_nymph[row] = sum((vector.matrix[,1]==0 & vector.matrix[,2]==1) | (vector.matrix[,1]==0 & vector.matrix[,2]==2));
|
|
|
1158 # For total nymph life stage of generation F1 population
|
|
|
1159 # size, one of the following combinations is required:
|
|
|
1160 # - column 1 (Generation) is 1 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1161 # - column 1 (Generation) is 1 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1162 F1.total_nymph[row] = sum((vector.matrix[,1]==1 & vector.matrix[,2]==1) | (vector.matrix[,1]==1 & vector.matrix[,2]==2));
|
|
|
1163 # For total nymph life stage of generation F2 population
|
|
|
1164 # size, one of the following combinations is required:
|
|
|
1165 # - column 1 (Generation) is 2 and column 2 (Stage) is 1 (Young nymph)
|
|
|
1166 # - column 1 (Generation) is 2 and column 2 (Stage) is 2 (Old nymph)
|
|
|
1167 F2.total_nymph[row] = sum((vector.matrix[,1]==2 & vector.matrix[,2]==1) | (vector.matrix[,1]==2 & vector.matrix[,2]==2));
|
|
|
1168 }
|
|
|
1169 if (process_previttelogenic_adults) {
|
|
|
1170 # For previttelogenic adult life stage of generation P population
|
|
|
1171 # size, the following combination is required:
|
|
|
1172 # - column 1 (Generation) is 0 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1173 P.previttelogenic_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==3);
|
|
|
1174 # For previttelogenic adult life stage of generation F1 population
|
|
|
1175 # size, the following combination is required:
|
|
|
1176 # - column 1 (Generation) is 1 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1177 F1.previttelogenic_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==3);
|
|
|
1178 # For previttelogenic adult life stage of generation F2 population
|
|
|
1179 # size, the following combination is required:
|
|
|
1180 # - column 1 (Generation) is 2 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1181 F2.previttelogenic_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==3);
|
|
|
1182 }
|
|
|
1183 if (process_vittelogenic_adults) {
|
|
|
1184 # For vittelogenic adult life stage of generation P population
|
|
|
1185 # size, the following combination is required:
|
|
|
1186 # - column 1 (Generation) is 0 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1187 P.vittelogenic_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==4);
|
|
|
1188 # For vittelogenic adult life stage of generation F1 population
|
|
|
1189 # size, the following combination is required:
|
|
|
1190 # - column 1 (Generation) is 1 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1191 F1.vittelogenic_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==4);
|
|
|
1192 # For vittelogenic adult life stage of generation F2 population
|
|
|
1193 # size, the following combination is required:
|
|
|
1194 # - column 1 (Generation) is 2 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1195 F2.vittelogenic_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==4);
|
|
|
1196 }
|
|
|
1197 if (process_diapausing_adults) {
|
|
|
1198 # For diapausing adult life stage of generation P population
|
|
|
1199 # size, the following combination is required:
|
|
|
1200 # - column 1 (Generation) is 0 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1201 P.diapausing_adult[row] = sum(vector.matrix[,1]==0 & vector.matrix[,2]==5);
|
|
|
1202 # For diapausing adult life stage of generation F1 population
|
|
|
1203 # size, the following combination is required:
|
|
|
1204 # - column 1 (Generation) is 1 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1205 F1.diapausing_adult[row] = sum(vector.matrix[,1]==1 & vector.matrix[,2]==5);
|
|
|
1206 # For diapausing adult life stage of generation F2 population
|
|
|
1207 # size, the following combination is required:
|
|
|
1208 # - column 1 (Generation) is 2 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1209 F2.diapausing_adult[row] = sum(vector.matrix[,1]==2 & vector.matrix[,2]==5);
|
|
|
1210 }
|
|
|
1211 if (process_total_adults) {
|
|
|
1212 # For total adult life stage of generation P population
|
|
|
1213 # size, one of the following combinations is required:
|
|
|
1214 # - column 1 (Generation) is 0 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1215 # - column 1 (Generation) is 0 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1216 # - column 1 (Generation) is 0 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1217 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));
|
|
|
1218 # For total adult life stage of generation F1 population
|
|
|
1219 # size, one of the following combinations is required:
|
|
|
1220 # - column 1 (Generation) is 1 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1221 # - column 1 (Generation) is 1 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1222 # - column 1 (Generation) is 1 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1223 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));
|
|
|
1224 # For total adult life stage of generation F2 population
|
|
|
1225 # size, one of the following combinations is required:
|
|
|
1226 # - column 1 (Generation) is 2 and column 2 (Stage) is 3 (Pre-vittelogenic)
|
|
|
1227 # - column 1 (Generation) is 2 and column 2 (Stage) is 4 (Vittelogenic)
|
|
|
1228 # - column 1 (Generation) is 2 and column 2 (Stage) is 5 (Diapausing)
|
|
|
1229 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));
|
|
|
1230 }
|
|
|
1231 }
|
|
|
1232 } # End of days specified in the input_ytd temperature data.
|
|
85
|
1233
|
|
131
|
1234 # Set the cumulative average temperature (this is never used).
|
|
111
|
1235 averages.cum = cumsum(averages.day);
|
|
85
|
1236
|
|
102
|
1237 # Define the output values.
|
|
112
|
1238 if (process_eggs) {
|
|
|
1239 Eggs.replications[,current_replication] = Eggs;
|
|
|
1240 }
|
|
|
1241 if (process_young_nymphs | process_total_nymphs) {
|
|
|
1242 YoungNymphs.replications[,current_replication] = YoungNymphs;
|
|
|
1243 }
|
|
|
1244 if (process_old_nymphs | process_total_nymphs) {
|
|
|
1245 OldNymphs.replications[,current_replication] = OldNymphs;
|
|
|
1246 }
|
|
|
1247 if (process_previttelogenic_adults | process_total_adults) {
|
|
|
1248 Previttelogenic.replications[,current_replication] = Previttelogenic;
|
|
|
1249 }
|
|
|
1250 if (process_vittelogenic_adults | process_total_adults) {
|
|
|
1251 Vittelogenic.replications[,current_replication] = Vittelogenic;
|
|
|
1252 }
|
|
|
1253 if (process_diapausing_adults | process_total_adults) {
|
|
|
1254 Diapausing.replications[,current_replication] = Diapausing;
|
|
|
1255 }
|
|
|
1256 newborn.replications[,current_replication] = N.newborn;
|
|
|
1257 adult.replications[,current_replication] = N.adult;
|
|
|
1258 death.replications[,current_replication] = N.death;
|
|
|
1259 if (plot_generations_separately) {
|
|
|
1260 # P is Parental, or overwintered adults.
|
|
|
1261 P.replications[,current_replication] = overwintering_adult.population;
|
|
|
1262 # F1 is the first field-produced generation.
|
|
|
1263 F1.replications[,current_replication] = first_generation.population;
|
|
|
1264 # F2 is the second field-produced generation.
|
|
|
1265 F2.replications[,current_replication] = second_generation.population;
|
|
|
1266 if (process_eggs) {
|
|
|
1267 P_eggs.replications[,current_replication] = P.egg;
|
|
|
1268 F1_eggs.replications[,current_replication] = F1.egg;
|
|
|
1269 F2_eggs.replications[,current_replication] = F2.egg;
|
|
|
1270 }
|
|
|
1271 if (process_young_nymphs) {
|
|
|
1272 P_young_nymphs.replications[,current_replication] = P.young_nymph;
|
|
|
1273 F1_young_nymphs.replications[,current_replication] = F1.young_nymph;
|
|
|
1274 F2_young_nymphs.replications[,current_replication] = F2.young_nymph;
|
|
|
1275 }
|
|
|
1276 if (process_old_nymphs) {
|
|
|
1277 P_old_nymphs.replications[,current_replication] = P.old_nymph;
|
|
|
1278 F1_old_nymphs.replications[,current_replication] = F1.old_nymph;
|
|
|
1279 F2_old_nymphs.replications[,current_replication] = F2.old_nymph;
|
|
|
1280 }
|
|
|
1281 if (process_total_nymphs) {
|
|
|
1282 P_total_nymphs.replications[,current_replication] = P.total_nymph;
|
|
|
1283 F1_total_nymphs.replications[,current_replication] = F1.total_nymph;
|
|
|
1284 F2_total_nymphs.replications[,current_replication] = F2.total_nymph;
|
|
|
1285 }
|
|
|
1286 if (process_previttelogenic_adults) {
|
|
|
1287 P_previttelogenic_adults.replications[,current_replication] = P.previttelogenic_adult;
|
|
|
1288 F1_previttelogenic_adults.replications[,current_replication] = F1.previttelogenic_adult;
|
|
|
1289 F2_previttelogenic_adults.replications[,current_replication] = F2.previttelogenic_adult;
|
|
|
1290 }
|
|
|
1291 if (process_vittelogenic_adults) {
|
|
|
1292 P_vittelogenic_adults.replications[,current_replication] = P.vittelogenic_adult;
|
|
|
1293 F1_vittelogenic_adults.replications[,current_replication] = F1.vittelogenic_adult;
|
|
|
1294 F2_vittelogenic_adults.replications[,current_replication] = F2.vittelogenic_adult;
|
|
|
1295 }
|
|
|
1296 if (process_diapausing_adults) {
|
|
|
1297 P_diapausing_adults.replications[,current_replication] = P.diapausing_adult;
|
|
|
1298 F1_diapausing_adults.replications[,current_replication] = F1.diapausing_adult;
|
|
|
1299 F2_diapausing_adults.replications[,current_replication] = F2.diapausing_adult;
|
|
|
1300 }
|
|
|
1301 if (process_total_adults) {
|
|
|
1302 P_total_adults.replications[,current_replication] = P.total_adult;
|
|
|
1303 F1_total_adults.replications[,current_replication] = F1.total_adult;
|
|
|
1304 F2_total_adults.replications[,current_replication] = F2.total_adult;
|
|
|
1305 }
|
|
|
1306 }
|
|
|
1307 population.replications[,current_replication] = total.population;
|
|
|
1308 # End processing replications.
|
|
|
1309 }
|
|
107
|
1310
|
|
131
|
1311 # Append the averages.day vector (i.e., degree-days)
|
|
|
1312 # to the various temperature_data_frames.
|
|
|
1313 temperature_data_frame = append_vector(temperature_data_frame, averages.day, "DEGREE.DAYS");
|
|
|
1314
|
|
112
|
1315 if (process_eggs) {
|
|
|
1316 # Mean value for eggs.
|
|
|
1317 eggs = apply(Eggs.replications, 1, mean);
|
|
|
1318 temperature_data_frame = append_vector(temperature_data_frame, eggs, "EGG");
|
|
|
1319 # Standard error for eggs.
|
|
|
1320 eggs.std_error = apply(Eggs.replications, 1, sd) / sqrt(opt$replications);
|
|
|
1321 temperature_data_frame = append_vector(temperature_data_frame, eggs.std_error, "EGGSE");
|
|
|
1322 }
|
|
|
1323 if (process_nymphs) {
|
|
|
1324 # Calculate nymph populations for selected life stage.
|
|
|
1325 for (life_stage_nymph in life_stages_nymph) {
|
|
|
1326 if (life_stage_nymph=="Young") {
|
|
|
1327 # Mean value for young nymphs.
|
|
|
1328 young_nymphs = apply(YoungNymphs.replications, 1, mean);
|
|
|
1329 temperature_data_frame = append_vector(temperature_data_frame, young_nymphs, "YOUNGNYMPH");
|
|
|
1330 # Standard error for young nymphs.
|
|
|
1331 young_nymphs.std_error = apply(YoungNymphs.replications / sqrt(opt$replications), 1, sd);
|
|
|
1332 temperature_data_frame = append_vector(temperature_data_frame, young_nymphs.std_error, "YOUNGNYMPHSE");
|
|
|
1333 } else if (life_stage_nymph=="Old") {
|
|
|
1334 # Mean value for old nymphs.
|
|
|
1335 old_nymphs = apply(OldNymphs.replications, 1, mean);
|
|
|
1336 temperature_data_frame = append_vector(temperature_data_frame, old_nymphs, "OLDNYMPH");
|
|
|
1337 # Standard error for old nymphs.
|
|
|
1338 old_nymphs.std_error = apply(OldNymphs.replications / sqrt(opt$replications), 1, sd);
|
|
|
1339 temperature_data_frame = append_vector(temperature_data_frame, old_nymphs.std_error, "OLDNYMPHSE");
|
|
|
1340 } else if (life_stage_nymph=="Total") {
|
|
|
1341 # Mean value for all nymphs.
|
|
|
1342 total_nymphs = apply((YoungNymphs.replications+OldNymphs.replications), 1, mean);
|
|
|
1343 temperature_data_frame = append_vector(temperature_data_frame, total_nymphs, "TOTALNYMPH");
|
|
|
1344 # Standard error for all nymphs.
|
|
|
1345 total_nymphs.std_error = apply((YoungNymphs.replications+OldNymphs.replications) / sqrt(opt$replications), 1, sd);
|
|
|
1346 temperature_data_frame = append_vector(temperature_data_frame, total_nymphs.std_error, "TOTALNYMPHSE");
|
|
|
1347 }
|
|
|
1348 }
|
|
|
1349 }
|
|
|
1350 if (process_adults) {
|
|
|
1351 # Calculate adult populations for selected life stage.
|
|
|
1352 for (life_stage_adult in life_stages_adult) {
|
|
|
1353 if (life_stage_adult == "Pre-vittelogenic") {
|
|
|
1354 # Mean value for previttelogenic adults.
|
|
|
1355 previttelogenic_adults = apply(Previttelogenic.replications, 1, mean);
|
|
125
|
1356 temperature_data_frame = append_vector(temperature_data_frame, previttelogenic_adults, "PRE.VITADULT");
|
|
112
|
1357 # Standard error for previttelogenic adults.
|
|
|
1358 previttelogenic_adults.std_error = apply(Previttelogenic.replications, 1, sd) / sqrt(opt$replications);
|
|
125
|
1359 temperature_data_frame = append_vector(temperature_data_frame, previttelogenic_adults.std_error, "PRE.VITADULTSE");
|
|
112
|
1360 } else if (life_stage_adult == "Vittelogenic") {
|
|
|
1361 # Mean value for vittelogenic adults.
|
|
|
1362 vittelogenic_adults = apply(Vittelogenic.replications, 1, mean);
|
|
|
1363 temperature_data_frame = append_vector(temperature_data_frame, vittelogenic_adults, "VITADULT");
|
|
|
1364 # Standard error for vittelogenic adults.
|
|
|
1365 vittelogenic_adults.std_error = apply(Vittelogenic.replications, 1, sd) / sqrt(opt$replications);
|
|
|
1366 temperature_data_frame = append_vector(temperature_data_frame, vittelogenic_adults.std_error, "VITADULTSE");
|
|
|
1367 } else if (life_stage_adult == "Diapausing") {
|
|
|
1368 # Mean value for vittelogenic adults.
|
|
|
1369 diapausing_adults = apply(Diapausing.replications, 1, mean);
|
|
|
1370 temperature_data_frame = append_vector(temperature_data_frame, diapausing_adults, "DIAPAUSINGADULT");
|
|
|
1371 # Standard error for vittelogenic adults.
|
|
|
1372 diapausing_adults.std_error = apply(Diapausing.replications, 1, sd) / sqrt(opt$replications);
|
|
|
1373 temperature_data_frame = append_vector(temperature_data_frame, diapausing_adults.std_error, "DIAPAUSINGADULTSE");
|
|
|
1374 } else if (life_stage_adult=="Total") {
|
|
|
1375 # Mean value for all adults.
|
|
|
1376 total_adults = apply((Previttelogenic.replications+Vittelogenic.replications+Diapausing.replications), 1, mean);
|
|
|
1377 temperature_data_frame = append_vector(temperature_data_frame, total_adults, "TOTALADULT");
|
|
|
1378 # Standard error for all adults.
|
|
|
1379 total_adults.std_error = apply((Previttelogenic.replications+Vittelogenic.replications+Diapausing.replications), 1, sd) / sqrt(opt$replications);
|
|
|
1380 temperature_data_frame = append_vector(temperature_data_frame, total_adults.std_error, "TOTALADULTSE");
|
|
|
1381 }
|
|
|
1382 }
|
|
85
|
1383 }
|
|
|
1384
|
|
112
|
1385 if (plot_generations_separately) {
|
|
131
|
1386 # Create copies of the temperature data for generations P, F1 and F2 if we're plotting generations separately.
|
|
|
1387 temperature_data_frame_P = data.frame(temperature_data_frame);
|
|
|
1388 temperature_data_frame_F1 = data.frame(temperature_data_frame);
|
|
|
1389 temperature_data_frame_F2 = data.frame(temperature_data_frame);
|
|
|
1390
|
|
112
|
1391 m_se = get_mean_and_std_error(P.replications, F1.replications, F2.replications);
|
|
|
1392 P = m_se[[1]];
|
|
|
1393 P.std_error = m_se[[2]];
|
|
|
1394 F1 = m_se[[3]];
|
|
|
1395 F1.std_error = m_se[[4]];
|
|
|
1396 F2 = m_se[[5]];
|
|
|
1397 F2.std_error = m_se[[6]];
|
|
|
1398 if (process_eggs) {
|
|
|
1399 m_se = get_mean_and_std_error(P_eggs.replications, F1_eggs.replications, F2_eggs.replications);
|
|
|
1400 P_eggs = m_se[[1]];
|
|
|
1401 P_eggs.std_error = m_se[[2]];
|
|
125
|
1402 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_eggs, "EGG.P");
|
|
|
1403 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_eggs.std_error, "EGG.P.SE");
|
|
112
|
1404 F1_eggs = m_se[[3]];
|
|
|
1405 F1_eggs.std_error = m_se[[4]];
|
|
125
|
1406 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_eggs, "EGG.F1");
|
|
|
1407 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_eggs.std_error, "EGG.F1.SE");
|
|
112
|
1408 F2_eggs = m_se[[5]];
|
|
|
1409 F2_eggs.std_error = m_se[[6]];
|
|
125
|
1410 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_eggs, "EGG.F2");
|
|
|
1411 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_eggs.std_error, "EGG.F2.SE");
|
|
112
|
1412 }
|
|
|
1413 if (process_young_nymphs) {
|
|
|
1414 m_se = get_mean_and_std_error(P_young_nymphs.replications, F1_young_nymphs.replications, F2_young_nymphs.replications);
|
|
|
1415 P_young_nymphs = m_se[[1]];
|
|
|
1416 P_young_nymphs.std_error = m_se[[2]];
|
|
125
|
1417 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_young_nymphs, "YOUNGNYMPH.P");
|
|
|
1418 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_young_nymphs.std_error, "YOUNGNYMPH.P.SE");
|
|
112
|
1419 F1_young_nymphs = m_se[[3]];
|
|
|
1420 F1_young_nymphs.std_error = m_se[[4]];
|
|
125
|
1421 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_young_nymphs, "YOUNGNYMPH.F1");
|
|
|
1422 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_young_nymphs.std_error, "YOUNGNYMPH.F1.SE");
|
|
112
|
1423 F2_young_nymphs = m_se[[5]];
|
|
|
1424 F2_young_nymphs.std_error = m_se[[6]];
|
|
125
|
1425 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_young_nymphs, "YOUNGNYMPH.F2");
|
|
|
1426 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_young_nymphs.std_error, "YOUNGNYMPH.F2.SE");
|
|
112
|
1427 }
|
|
|
1428 if (process_old_nymphs) {
|
|
|
1429 m_se = get_mean_and_std_error(P_old_nymphs.replications, F1_old_nymphs.replications, F2_old_nymphs.replications);
|
|
|
1430 P_old_nymphs = m_se[[1]];
|
|
|
1431 P_old_nymphs.std_error = m_se[[2]];
|
|
125
|
1432 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_old_nymphs, "OLDNYMPH.P");
|
|
|
1433 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_old_nymphs.std_error, "OLDNYMPH.P.SE");
|
|
112
|
1434 F1_old_nymphs = m_se[[3]];
|
|
|
1435 F1_old_nymphs.std_error = m_se[[4]];
|
|
125
|
1436 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_old_nymphs, "OLDNYMPH.F1");
|
|
|
1437 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_old_nymphs.std_error, "OLDNYMPH.F1.SE");
|
|
112
|
1438 F2_old_nymphs = m_se[[5]];
|
|
|
1439 F2_old_nymphs.std_error = m_se[[6]];
|
|
125
|
1440 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_old_nymphs, "OLDNYMPH.F2");
|
|
|
1441 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_old_nymphs.std_error, "OLDNYMPH.F2.SE");
|
|
112
|
1442 }
|
|
|
1443 if (process_total_nymphs) {
|
|
|
1444 m_se = get_mean_and_std_error(P_total_nymphs.replications, F1_total_nymphs.replications, F2_total_nymphs.replications);
|
|
|
1445 P_total_nymphs = m_se[[1]];
|
|
|
1446 P_total_nymphs.std_error = m_se[[2]];
|
|
125
|
1447 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_nymphs, "TOTALNYMPH.P");
|
|
|
1448 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_nymphs.std_error, "TOTALNYMPH.P.SE");
|
|
112
|
1449 F1_total_nymphs = m_se[[3]];
|
|
|
1450 F1_total_nymphs.std_error = m_se[[4]];
|
|
125
|
1451 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_nymphs, "TOTALNYMPH.F1");
|
|
|
1452 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_nymphs.std_error, "TOTALNYMPH.F1.SE");
|
|
112
|
1453 F2_total_nymphs = m_se[[5]];
|
|
|
1454 F2_total_nymphs.std_error = m_se[[6]];
|
|
125
|
1455 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_nymphs, "TOTALNYMPH.F2");
|
|
|
1456 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_nymphs.std_error, "TOTALNYMPH.F2.SE");
|
|
112
|
1457 }
|
|
|
1458 if (process_previttelogenic_adults) {
|
|
|
1459 m_se = get_mean_and_std_error(P_previttelogenic_adults.replications, F1_previttelogenic_adults.replications, F2_previttelogenic_adults.replications);
|
|
|
1460 P_previttelogenic_adults = m_se[[1]];
|
|
|
1461 P_previttelogenic_adults.std_error = m_se[[2]];
|
|
125
|
1462 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_previttelogenic_adults, "PRE.VITADULT.P");
|
|
|
1463 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_previttelogenic_adults.std_error, "PRE.VITADULT.P.SE");
|
|
112
|
1464 F1_previttelogenic_adults = m_se[[3]];
|
|
|
1465 F1_previttelogenic_adults.std_error = m_se[[4]];
|
|
125
|
1466 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_previttelogenic_adults, "PRE.VITADULT.F1");
|
|
|
1467 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_previttelogenic_adults.std_error, "PRE.VITADULT.F1.SE");
|
|
112
|
1468 F2_previttelogenic_adults = m_se[[5]];
|
|
|
1469 F2_previttelogenic_adults.std_error = m_se[[6]];
|
|
125
|
1470 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_previttelogenic_adults, "PRE.VITADULT.F2");
|
|
|
1471 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_previttelogenic_adults.std_error, "PRE.VITADULT.F2.SE");
|
|
112
|
1472 }
|
|
|
1473 if (process_vittelogenic_adults) {
|
|
|
1474 m_se = get_mean_and_std_error(P_vittelogenic_adults.replications, F1_vittelogenic_adults.replications, F2_vittelogenic_adults.replications);
|
|
|
1475 P_vittelogenic_adults = m_se[[1]];
|
|
|
1476 P_vittelogenic_adults.std_error = m_se[[2]];
|
|
125
|
1477 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_vittelogenic_adults, "VITADULT.P");
|
|
|
1478 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_vittelogenic_adults.std_error, "VITADULT.P.SE");
|
|
112
|
1479 F1_vittelogenic_adults = m_se[[3]];
|
|
|
1480 F1_vittelogenic_adults.std_error = m_se[[4]];
|
|
125
|
1481 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_vittelogenic_adults, "VITADULT.F1");
|
|
|
1482 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_vittelogenic_adults.std_error, "VITADULT.F1.SE");
|
|
112
|
1483 F2_vittelogenic_adults = m_se[[5]];
|
|
|
1484 F2_vittelogenic_adults.std_error = m_se[[6]];
|
|
125
|
1485 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_vittelogenic_adults, "VITADULT.F2");
|
|
|
1486 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_vittelogenic_adults.std_error, "VITADULT.F2.SE");
|
|
112
|
1487 }
|
|
|
1488 if (process_diapausing_adults) {
|
|
|
1489 m_se = get_mean_and_std_error(P_diapausing_adults.replications, F1_diapausing_adults.replications, F2_diapausing_adults.replications);
|
|
|
1490 P_diapausing_adults = m_se[[1]];
|
|
|
1491 P_diapausing_adults.std_error = m_se[[2]];
|
|
125
|
1492 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_diapausing_adults, "DIAPAUSINGADULT.P");
|
|
|
1493 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_diapausing_adults.std_error, "DIAPAUSINGADULT.P.SE");
|
|
112
|
1494 F1_diapausing_adults = m_se[[3]];
|
|
|
1495 F1_diapausing_adults.std_error = m_se[[4]];
|
|
125
|
1496 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_diapausing_adults, "DIAPAUSINGADULT.F1");
|
|
|
1497 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_diapausing_adults.std_error, "DIAPAUSINGADULT.F1.SE");
|
|
112
|
1498 F2_diapausing_adults = m_se[[5]];
|
|
|
1499 F2_diapausing_adults.std_error = m_se[[6]];
|
|
125
|
1500 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_diapausing_adults, "DIAPAUSINGADULT.F2");
|
|
|
1501 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_diapausing_adults.std_error, "DIAPAUSINGADULT.F2.SE");
|
|
112
|
1502 }
|
|
|
1503 if (process_total_adults) {
|
|
|
1504 m_se = get_mean_and_std_error(P_total_adults.replications, F1_total_adults.replications, F2_total_adults.replications);
|
|
|
1505 P_total_adults = m_se[[1]];
|
|
|
1506 P_total_adults.std_error = m_se[[2]];
|
|
125
|
1507 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_adults, "TOTALADULT.P");
|
|
|
1508 temperature_data_frame_P = append_vector(temperature_data_frame_P, P_total_adults.std_error, "TOTALADULT.P.SE");
|
|
112
|
1509 F1_total_adults = m_se[[3]];
|
|
|
1510 F1_total_adults.std_error = m_se[[4]];
|
|
125
|
1511 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_adults, "TOTALADULT.F1");
|
|
|
1512 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1_total_adults.std_error, "TOTALADULT.F1.SE");
|
|
112
|
1513 F2_total_adults = m_se[[5]];
|
|
|
1514 F2_total_adults.std_error = m_se[[6]];
|
|
125
|
1515 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_adults, "TOTALADULT.F2");
|
|
|
1516 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2_total_adults.std_error, "TOTALADULT.F2.SE");
|
|
112
|
1517 }
|
|
126
|
1518 if (process_total) {
|
|
|
1519 temperature_data_frame_P = append_vector(temperature_data_frame_P, P, "ALL.TOTAL.P");
|
|
|
1520 temperature_data_frame_P = append_vector(temperature_data_frame_P, P.std_error, "ALL.TOTAL.P.SE");
|
|
|
1521 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1, "ALL.TOTAL.F1");
|
|
|
1522 temperature_data_frame_F1 = append_vector(temperature_data_frame_F1, F1.std_error, "ALL.TOTAL.F1.SE");
|
|
|
1523 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2, "ALL.TOTAL.F2");
|
|
|
1524 temperature_data_frame_F2 = append_vector(temperature_data_frame_F2, F2.std_error, "ALL.TOTAL.F2.SE");
|
|
|
1525 }
|
|
112
|
1526 }
|
|
103
|
1527
|
|
112
|
1528 # Save the analyzed data for combined generations.
|
|
|
1529 file_path = paste("output_data_dir", "04_combined_generations.csv", sep="/");
|
|
|
1530 write.csv(temperature_data_frame, file=file_path, row.names=F);
|
|
|
1531 if (plot_generations_separately) {
|
|
|
1532 # Save the analyzed data for generation P.
|
|
|
1533 file_path = paste("output_data_dir", "01_generation_P.csv", sep="/");
|
|
|
1534 write.csv(temperature_data_frame_P, file=file_path, row.names=F);
|
|
|
1535 # Save the analyzed data for generation F1.
|
|
|
1536 file_path = paste("output_data_dir", "02_generation_F1.csv", sep="/");
|
|
|
1537 write.csv(temperature_data_frame_F1, file=file_path, row.names=F);
|
|
|
1538 # Save the analyzed data for generation F2.
|
|
|
1539 file_path = paste("output_data_dir", "03_generation_F2.csv", sep="/");
|
|
|
1540 write.csv(temperature_data_frame_F2, file=file_path, row.names=F);
|
|
|
1541 }
|
|
103
|
1542
|
|
135
|
1543 # Get the ticks date labels for plots.
|
|
|
1544 ticks_and_labels = get_x_axis_ticks_and_labels(temperature_data_frame, prepend_end_doy_norm, append_start_doy_norm, doy_zero_insects);
|
|
|
1545 ticks = c(unlist(ticks_and_labels[1]));
|
|
|
1546 date_labels = c(unlist(ticks_and_labels[2]));
|
|
122
|
1547 total_days_vector = c(1:dim(temperature_data_frame)[1]);
|
|
135
|
1548
|
|
112
|
1549 if (plot_generations_separately) {
|
|
|
1550 for (life_stage in life_stages) {
|
|
|
1551 if (life_stage == "Egg") {
|
|
|
1552 # Start PDF device driver.
|
|
|
1553 dev.new(width=20, height=30);
|
|
|
1554 file_path = get_file_path(life_stage, "egg_pop_by_generation.pdf")
|
|
|
1555 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1556 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1557 # Egg population size by generation.
|
|
|
1558 maxval = max(P_eggs+F1_eggs+F2_eggs) + 100;
|
|
|
1559 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1560 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=P_eggs, group_std_error=P_eggs.std_error,
|
|
|
1561 group2=F1_eggs, group2_std_error=F1_eggs.std_error, group3=F2_eggs, group3_std_error=F2_eggs.std_error);
|
|
|
1562 # Turn off device driver to flush output.
|
|
|
1563 dev.off();
|
|
|
1564 } else if (life_stage == "Nymph") {
|
|
|
1565 for (life_stage_nymph in life_stages_nymph) {
|
|
|
1566 # Start PDF device driver.
|
|
|
1567 dev.new(width=20, height=30);
|
|
125
|
1568 file_path = get_file_path(life_stage, "nymph_pop_by_generation.pdf", sub_life_stage=life_stage_nymph)
|
|
112
|
1569 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1570 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1571 if (life_stage_nymph=="Young") {
|
|
|
1572 # Young nymph population size by generation.
|
|
|
1573 maxval = max(P_young_nymphs+F1_young_nymphs+F2_young_nymphs) + 100;
|
|
|
1574 group = P_young_nymphs;
|
|
|
1575 group_std_error = P_young_nymphs.std_error;
|
|
|
1576 group2 = F1_young_nymphs;
|
|
|
1577 group2_std_error = F1_young_nymphs.std_error;
|
|
|
1578 group3 = F2_young_nymphs;
|
|
|
1579 group3_std_error = F2_young_nymphs.std_error;
|
|
|
1580 } else if (life_stage_nymph=="Old") {
|
|
|
1581 # Total nymph population size by generation.
|
|
|
1582 maxval = max(P_old_nymphs+F1_old_nymphs+F2_old_nymphs) + 100;
|
|
|
1583 group = P_old_nymphs;
|
|
|
1584 group_std_error = P_old_nymphs.std_error;
|
|
|
1585 group2 = F1_old_nymphs;
|
|
|
1586 group2_std_error = F1_old_nymphs.std_error;
|
|
|
1587 group3 = F2_old_nymphs;
|
|
|
1588 group3_std_error = F2_old_nymphs.std_error;
|
|
|
1589 } else if (life_stage_nymph=="Total") {
|
|
|
1590 # Total nymph population size by generation.
|
|
|
1591 maxval = max(P_total_nymphs+F1_total_nymphs+F2_total_nymphs) + 100;
|
|
|
1592 group = P_total_nymphs;
|
|
|
1593 group_std_error = P_total_nymphs.std_error;
|
|
|
1594 group2 = F1_total_nymphs;
|
|
|
1595 group2_std_error = F1_total_nymphs.std_error;
|
|
|
1596 group3 = F2_total_nymphs;
|
|
|
1597 group3_std_error = F2_total_nymphs.std_error;
|
|
|
1598 }
|
|
|
1599 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1600 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
|
|
125
|
1601 group2=group2, group2_std_error=group2_std_error, group3=group3, group3_std_error=group3_std_error, sub_life_stage=life_stage_nymph);
|
|
112
|
1602 # Turn off device driver to flush output.
|
|
|
1603 dev.off();
|
|
|
1604 }
|
|
|
1605 } else if (life_stage == "Adult") {
|
|
|
1606 for (life_stage_adult in life_stages_adult) {
|
|
|
1607 # Start PDF device driver.
|
|
|
1608 dev.new(width=20, height=30);
|
|
125
|
1609 file_path = get_file_path(life_stage, "adult_pop_by_generation.pdf", sub_life_stage=life_stage_adult)
|
|
112
|
1610 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1611 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1612 if (life_stage_adult=="Pre-vittelogenic") {
|
|
|
1613 # Pre-vittelogenic adult population size by generation.
|
|
|
1614 maxval = max(P_previttelogenic_adults+F1_previttelogenic_adults+F2_previttelogenic_adults) + 100;
|
|
|
1615 group = P_previttelogenic_adults;
|
|
|
1616 group_std_error = P_previttelogenic_adults.std_error;
|
|
|
1617 group2 = F1_previttelogenic_adults;
|
|
|
1618 group2_std_error = F1_previttelogenic_adults.std_error;
|
|
|
1619 group3 = F2_previttelogenic_adults;
|
|
|
1620 group3_std_error = F2_previttelogenic_adults.std_error;
|
|
|
1621 } else if (life_stage_adult=="Vittelogenic") {
|
|
|
1622 # Vittelogenic adult population size by generation.
|
|
|
1623 maxval = max(P_vittelogenic_adults+F1_vittelogenic_adults+F2_vittelogenic_adults) + 100;
|
|
|
1624 group = P_vittelogenic_adults;
|
|
|
1625 group_std_error = P_vittelogenic_adults.std_error;
|
|
|
1626 group2 = F1_vittelogenic_adults;
|
|
|
1627 group2_std_error = F1_vittelogenic_adults.std_error;
|
|
|
1628 group3 = F2_vittelogenic_adults;
|
|
|
1629 group3_std_error = F2_vittelogenic_adults.std_error;
|
|
|
1630 } else if (life_stage_adult=="Diapausing") {
|
|
|
1631 # Diapausing adult population size by generation.
|
|
|
1632 maxval = max(P_diapausing_adults+F1_diapausing_adults+F2_diapausing_adults) + 100;
|
|
|
1633 group = P_diapausing_adults;
|
|
|
1634 group_std_error = P_diapausing_adults.std_error;
|
|
|
1635 group2 = F1_diapausing_adults;
|
|
|
1636 group2_std_error = F1_diapausing_adults.std_error;
|
|
|
1637 group3 = F2_diapausing_adults;
|
|
|
1638 group3_std_error = F2_diapausing_adults.std_error;
|
|
|
1639 } else if (life_stage_adult=="Total") {
|
|
|
1640 # Total adult population size by generation.
|
|
|
1641 maxval = max(P_total_adults+F1_total_adults+F2_total_adults) + 100;
|
|
|
1642 group = P_total_adults;
|
|
|
1643 group_std_error = P_total_adults.std_error;
|
|
|
1644 group2 = F1_total_adults;
|
|
|
1645 group2_std_error = F1_total_adults.std_error;
|
|
|
1646 group3 = F2_total_adults;
|
|
|
1647 group3_std_error = F2_total_adults.std_error;
|
|
|
1648 }
|
|
|
1649 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1650 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
|
|
125
|
1651 group2=group2, group2_std_error=group2_std_error, group3=group3, group3_std_error=group3_std_error, sub_life_stage=life_stage_adult);
|
|
112
|
1652 # Turn off device driver to flush output.
|
|
|
1653 dev.off();
|
|
|
1654 }
|
|
|
1655 } else if (life_stage == "Total") {
|
|
|
1656 # Start PDF device driver.
|
|
|
1657 # Name collection elements so that they
|
|
|
1658 # are displayed in logical order.
|
|
|
1659 dev.new(width=20, height=30);
|
|
|
1660 file_path = get_file_path(life_stage, "total_pop_by_generation.pdf")
|
|
|
1661 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1662 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1663 # Total population size by generation.
|
|
|
1664 maxval = max(P+F1+F2) + 100;
|
|
|
1665 render_chart(ticks, date_labels, "pop_size_by_generation", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1666 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=P, group_std_error=P.std_error,
|
|
|
1667 group2=F1, group2_std_error=F1.std_error, group3=F2, group3_std_error=F2.std_error);
|
|
|
1668 # Turn off device driver to flush output.
|
|
|
1669 dev.off();
|
|
|
1670 }
|
|
|
1671 }
|
|
|
1672 } else {
|
|
|
1673 for (life_stage in life_stages) {
|
|
|
1674 if (life_stage == "Egg") {
|
|
|
1675 # Start PDF device driver.
|
|
|
1676 dev.new(width=20, height=30);
|
|
|
1677 file_path = get_file_path(life_stage, "egg_pop.pdf")
|
|
|
1678 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1679 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1680 # Egg population size.
|
|
|
1681 maxval = max(eggs+eggs.std_error) + 100;
|
|
|
1682 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1683 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=eggs, group_std_error=eggs.std_error);
|
|
|
1684 # Turn off device driver to flush output.
|
|
|
1685 dev.off();
|
|
|
1686 } else if (life_stage == "Nymph") {
|
|
|
1687 for (life_stage_nymph in life_stages_nymph) {
|
|
|
1688 # Start PDF device driver.
|
|
|
1689 dev.new(width=20, height=30);
|
|
125
|
1690 file_path = get_file_path(life_stage, "nymph_pop.pdf", sub_life_stage=life_stage_nymph)
|
|
112
|
1691 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1692 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1693 if (life_stage_nymph=="Total") {
|
|
|
1694 # Total nymph population size.
|
|
|
1695 group = total_nymphs;
|
|
|
1696 group_std_error = total_nymphs.std_error;
|
|
|
1697 } else if (life_stage_nymph=="Young") {
|
|
|
1698 # Young nymph population size.
|
|
|
1699 group = young_nymphs;
|
|
|
1700 group_std_error = young_nymphs.std_error;
|
|
|
1701 } else if (life_stage_nymph=="Old") {
|
|
|
1702 # Old nymph population size.
|
|
|
1703 group = old_nymphs;
|
|
|
1704 group_std_error = old_nymphs.std_error;
|
|
|
1705 }
|
|
|
1706 maxval = max(group+group_std_error) + 100;
|
|
|
1707 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1708 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
|
|
125
|
1709 sub_life_stage=life_stage_nymph);
|
|
112
|
1710 # Turn off device driver to flush output.
|
|
|
1711 dev.off();
|
|
|
1712 }
|
|
|
1713 } else if (life_stage == "Adult") {
|
|
|
1714 for (life_stage_adult in life_stages_adult) {
|
|
|
1715 # Start PDF device driver.
|
|
|
1716 dev.new(width=20, height=30);
|
|
125
|
1717 file_path = get_file_path(life_stage, "adult_pop.pdf", sub_life_stage=life_stage_adult)
|
|
112
|
1718 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1719 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1720 if (life_stage_adult=="Total") {
|
|
|
1721 # Total adult population size.
|
|
|
1722 group = total_adults;
|
|
|
1723 group_std_error = total_adults.std_error
|
|
|
1724 } else if (life_stage_adult=="Pre-vittelogenic") {
|
|
|
1725 # Pre-vittelogenic adult population size.
|
|
|
1726 group = previttelogenic_adults;
|
|
|
1727 group_std_error = previttelogenic_adults.std_error
|
|
|
1728 } else if (life_stage_adult=="Vittelogenic") {
|
|
|
1729 # Vittelogenic adult population size.
|
|
|
1730 group = vittelogenic_adults;
|
|
|
1731 group_std_error = vittelogenic_adults.std_error
|
|
|
1732 } else if (life_stage_adult=="Diapausing") {
|
|
|
1733 # Diapausing adult population size.
|
|
|
1734 group = diapausing_adults;
|
|
|
1735 group_std_error = diapausing_adults.std_error
|
|
|
1736 }
|
|
|
1737 maxval = max(group+group_std_error) + 100;
|
|
|
1738 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1739 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=group, group_std_error=group_std_error,
|
|
125
|
1740 sub_life_stage=life_stage_adult);
|
|
112
|
1741 # Turn off device driver to flush output.
|
|
|
1742 dev.off();
|
|
|
1743 }
|
|
|
1744 } else if (life_stage == "Total") {
|
|
|
1745 # Start PDF device driver.
|
|
|
1746 dev.new(width=20, height=30);
|
|
|
1747 file_path = get_file_path(life_stage, "total_pop.pdf")
|
|
|
1748 pdf(file=file_path, width=20, height=30, bg="white");
|
|
|
1749 par(mar=c(5, 6, 4, 4), mfrow=c(3, 1));
|
|
|
1750 # Total population size.
|
|
|
1751 maxval = max(eggs+eggs.std_error, total_nymphs+total_nymphs.std_error, total_adults+total_adults.std_error) + 100;
|
|
|
1752 render_chart(ticks, date_labels, "pop_size_by_life_stage", opt$plot_std_error, opt$insect, location, latitude,
|
|
|
1753 start_date, end_date, total_days_vector, maxval, opt$replications, life_stage, group=total_adults, group_std_error=total_adults.std_error,
|
|
|
1754 group2=total_nymphs, group2_std_error=total_nymphs.std_error, group3=eggs, group3_std_error=eggs.std_error);
|
|
|
1755 # Turn off device driver to flush output.
|
|
|
1756 dev.off();
|
|
|
1757 }
|
|
|
1758 }
|
|
|
1759 }
|
