comparison insect_phenology_model.R @ 49:1b6864c5b50a draft

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48:99e1c1300fcd

option_list <- list(
    make_option(c("--adult_mortality"), action="store", dest="adult_mortality", type="integer", help="Adjustment rate for adult mortality"),
    make_option(c("--adult_accumulation"), action="store", dest="adult_accumulation", type="integer", help="Adjustment of degree-days accumulation (old nymph->adult)"),
    make_option(c("--egg_mortality"), action="store", dest="egg_mortality", type="integer", help="Adjustment rate for egg mortality"),
    make_option(c("--input_norm"), action="store", dest="input_norm", help="30 year normals temperature data for selected station"),
    make_option(c("--input_ytd"), action="store", dest="input_ytd", default=NULL, help="Year-to-date temperature data for selected location"),
    make_option(c("--insect"), action="store", dest="insect", help="Insect name"),
    make_option(c("--insects_per_replication"), action="store", dest="insects_per_replication", type="integer", help="Number of insects with which to start each replication"),
    make_option(c("--life_stages"), action="store", dest="life_stages", help="Selected life stages for plotting"),

    make_option(c("--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"),
    make_option(c("--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"),
    make_option(c("--plot_generations_separately"), action="store", dest="plot_generations_separately", help="Plot Plot P, F1 and F2 as separate lines or pool across them"),
    make_option(c("--plot_std_error"), action="store", dest="plot_std_error", help="Plot Standard error"),
    make_option(c("--replications"), action="store", dest="replications", type="integer", help="Number of replications"),
    make_option(c("--young_nymph_accumulation"), action="store", dest="young_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (egg->young nymph)")
)

parser <- OptionParser(usage="%prog [options] file", option_list=option_list);
args <- parse_args(parser, positional_arguments=TRUE);
opt <- args$options;

add_daylight_length = function(temperature_data_frame, num_rows) {
    # Return a vector of daylight length (photoperido profile) for
    # the number of days specified in the input_ytd temperature data
    # (from Forsythe 1995).
    p = 0.8333;
    latitude = temperature_data_frame$LATITUDE[1];
    daylight_length_vector = NULL;
    for (i in 1:num_rows) {
        # Get the day of the year from the current row

    # Append vector vec as a new column to data_frame.
    data_frame[,num_columns+1] = vec;
    # Reset the column names with the additional column for later access.
    colnames(data_frame) = append(current_column_names, new_column_name);
    return(data_frame);
}

get_file_path = function(life_stage, base_name, life_stage_nymph=NULL, life_stage_adult=NULL) {
    if (!is.null(life_stage_nymph)) {
        lsi = get_life_stage_index(life_stage, life_stage_nymph=life_stage_nymph);

    # F2 standard error.
    f2_se = apply(f2_replications, 1, sd) / sqrt(opt$replications);
    return(list(p_m, p_se, f1_m, f1_se, f2_m, f2_se))
}

get_next_normals_row = function(norm_data_frame, year, is_leap_year, index) {
    # Return the next 30 year normals row formatted
    # appropriately for the year-to-date data.
    latitude = norm_data_frame[index,"LATITUDE"][1];
    longitude = norm_data_frame[index,"LONGITUDE"][1];
    # Format the date.
    mmdd = norm_data_frame[index,"MMDD"][1];
    date_str = paste(year, mmdd, sep="-");
    doy = norm_data_frame[index,"DOY"][1];
    if (!is_leap_year) {
        # Since all normals data includes Feb 29, we have to
        # subtract 1 from DOY if we're not in a leap year since
        # we removed the Feb 29 row from the data frame above.
        doy = as.integer(doy) - 1;
    }
    tmin = norm_data_frame[index,"TMIN"][1];
    tmax = norm_data_frame[index,"TMAX"][1];
    return(list(latitude, longitude, date_str, doy, tmin, tmax));
}

get_temperature_at_hour = function(latitude, temperature_data_frame, row, num_days) {
    # Base development threshold for Brown Marmorated Stink Bug
    # insect phenology model.
    threshold = 14.17;
    # Minimum temperature for current row.
    curr_min_temp = temperature_data_frame$TMIN[row];

        averages = sum(dh) / 24;
    }
    return(c(curr_mean_temp, averages))
}

get_tick_index = function(index, last_tick, ticks, month_labels) {
    # The R code tries hard not to draw overlapping tick labels, and so
    # will omit labels where they would abut or overlap previously drawn
    # labels. This can result in, for example, every other tick being
    # labelled.  We'll keep track of the last tick to make sure all of
    # the month labels are displayed, and missing ticks are restricted
    # to Sundays which have no labels anyway.
    if (last_tick==0) {
        return(length(ticks)+1);
    }
    last_saved_tick = ticks[[length(ticks)]];
    if (index-last_saved_tick<3) {
        last_saved_month = month_labels[[length(month_labels)]];
        if (last_saved_month=="") {
            # We're safe overwriting a tick
            # with no label (i.e., a Sunday tick).
            return(length(ticks));
        } else {

    } else {
        return(365);
    }
}

get_x_axis_ticks_and_labels = function(temperature_data_frame, num_rows, start_doy_ytd, end_doy_ytd) {
    # Keep track of the years to see if spanning years.
    month_labels = list();
    ticks = list();
    current_month_label = NULL;
    last_tick = 0;
    for (i in 1:num_rows) {
        if (start_doy_ytd > 1 & i==start_doy_ytd-1) {
            # Add a tick for the end of the 30 year normnals data
            # that was prepended to the year-to-date data.
            tick_index = get_tick_index(i, last_tick, ticks, month_labels)
            ticks[tick_index] = i;
            month_labels[tick_index] = "End prepended 30 year normals";
            last_tick = i;
        } else  if (end_doy_ytd > 0 & i==end_doy_ytd+1) {
            # Add a tick for the start of the 30 year normnals data
            # that was appended to the year-to-date data.
            tick_index = get_tick_index(i, last_tick, ticks, month_labels)
            ticks[tick_index] = i;
            month_labels[tick_index] = "Start appended 30 year normals";
            last_tick = i;
        } else if (i==num_rows) {
            # Add a tick for the last day of the year.
            tick_index = get_tick_index(i, last_tick, ticks, month_labels)
            ticks[tick_index] = i;
            month_labels[tick_index] = "";
            last_tick = i;
        } else {
            # Get the year and month from the date which
            # has the format YYYY-MM-DD.
            date = format(temperature_data_frame$DATE[i]);
            # Get the month label.
            items = strsplit(date, "-")[[1]];
            month = items[2];
            month_label = month.abb[as.integer(month)];
            if (!identical(current_month_label, month_label)) {
                # Add an x-axis tick for the month.
                tick_index = get_tick_index(i, last_tick, ticks, month_labels)
                ticks[tick_index] = i;
                month_labels[tick_index] = month_label;
                current_month_label = month_label;
                last_tick = i;
            }
            tick_index = get_tick_index(i, last_tick, ticks, month_labels)
            if (!is.null(tick_index)) {
                # Get the day.
                day = weekdays(as.Date(date));
                if (day=="Sunday") {
                    # Add an x-axis tick if we're on a Sunday.
                    ticks[tick_index] = i;
                    # Add a blank month label so it is not displayed.
                    month_labels[tick_index] = "";
                    last_tick = i;
                }
            }
        }
    }
    return(list(ticks, month_labels));
}

is_leap_year = function(date_str) {
    # Extract the year from the date_str.
    date = format(date_str);

        mortality.probability = temperature * 0.0008 + 0.03;
    }
    return(mortality.probability);
}

parse_input_data = function(input_ytd, input_norm, num_days_ytd, location) {
    if (is.null(input_ytd)) {
        # We're analysing only the 30 year normals data, so create an empty
        # data frame for containing temperature data after it is converted
        # from the 30 year normals format to the year-to-date format.
        temperature_data_frame = data.frame(matrix(ncol=6, nrow=0));
        colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
        # Base all dates on the current date since 30 year
        # normals data does not include any dates.
        year = format(Sys.Date(), "%Y");
        start_date = paste(year, "01", "01", sep="-");
        end_date = paste(year, "12", "31", sep="-");
        # Set invalid start and end DOY.
        start_doy_ytd = 0;
        end_doy_ytd = 0;
    } else {
        # Read the input_ytd temperature datafile into a data frame.
        # The input_ytd data has the following 6 columns:
        # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
        temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
        # Set the temperature_data_frame column names for access.
        colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
        # Get the start date.
        start_date = temperature_data_frame$DATE[1];
        end_date = temperature_data_frame$DATE[num_days_ytd];
        # Extract the year from the start date.
        date_str = format(start_date);
        date_str_items = strsplit(date_str, "-")[[1]];
        year = date_str_items[1];
        # Save the first DOY to later check if start_date is Jan 1.
        start_doy_ytd = as.integer(temperature_data_frame$DOY[1]);
        end_doy_ytd = as.integer(temperature_data_frame$DOY[num_days_ytd]);
    }
    # See if we're in a leap year.
    is_leap_year = is_leap_year(start_date);
    # Get the number of days in the year.
    total_days = get_total_days(is_leap_year);
    # Read the input_norm temperature datafile into a data frame.
    # The input_norm data has the following 10 columns:
    # STATIONID, LATITUDE, LONGITUDE, ELEV_M, NAME, ST, MMDD, DOY, TMIN, TMAX
    norm_data_frame = read.csv(file=input_norm, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
    # Set the norm_data_frame column names for access.
    colnames(norm_data_frame) = c("STATIONID", "LATITUDE","LONGITUDE", "ELEV_M", "NAME", "ST", "MMDD", "DOY", "TMIN", "TMAX");
    # All normals data includes Feb 29 which is row 60 in
    # the data, so delete that row if we're not in a leap year.
    if (!is_leap_year) {
        norm_data_frame = norm_data_frame[-c(60),];
    }
    # Set the location to be the station name if the user elected no to enter it.
    if (is.null(location) | length(location)==0) {
        location = norm_data_frame$NAME[1];
    }
    if (is.null(input_ytd)) {
        # Convert the 30 year normals data to the year-to-date format.
        for (i in 1:total_days) {
            temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, is_leap_year, i);
        }
    } else {
        # Merge the year-to-date data with the 30 year normals data.
        if (start_doy_ytd > 1) {
            # The year-to-date data starts after Jan 1, so create a
            # temporary data frame to contain the 30 year normals data
            # from Jan 1 to the date immediately prior to start_date.
            tmp_data_frame = temperature_data_frame[FALSE,];
            for (i in 1:start_doy_ytd-1) {
                tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, is_leap_year, i);
            }
            # Next merge the temporary data frame with the year-to-date data frame.
            temperature_data_frame = rbind(tmp_data_frame, temperature_data_frame);
        }
        # Define the next row for the year-to-date data from the 30 year normals data.
        first_normals_append_row = end_doy_ytd + 1;
        # Append the 30 year normals data to the year-to-date data.
        for (i in first_normals_append_row:total_days) {
            temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, is_leap_year, i);
        }
    }
    # Add a column containing the daylight length for each day.
    temperature_data_frame = add_daylight_length(temperature_data_frame, total_days);
    return(list(temperature_data_frame, start_date, end_date, start_doy_ytd, end_doy_ytd, is_leap_year, total_days, location));
}

render_chart = function(ticks, date_labels, chart_type, plot_std_error, insect, location, latitude, start_date, end_date, days, maxval,
    replications, life_stage, group, group_std_error, group2=NULL, group2_std_error=NULL, group3=NULL, group3_std_error=NULL,
    life_stages_adult=NULL, life_stages_nymph=NULL) {

            lines(days, group3-group3_std_error, col=4, lty=2);
        }
    }
}

# Determine if we're plotting generations separately.
if (opt$plot_generations_separately=="yes") {
    plot_generations_separately = TRUE;
} else {
    plot_generations_separately = FALSE;
}
# Display the total number of days in the Galaxy history item blurb.
cat("Year-to-date number of days: ", opt$num_days_ytd, "\n");

# Parse the inputs.
data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$num_days_ytd, opt$location);
temperature_data_frame = data_list[[1]];
# Information needed for plots.
start_date = data_list[[2]];
end_date = data_list[[3]];
start_doy_ytd = data_list[[4]];
end_doy_ytd = data_list[[5]];
is_leap_year = data_list[[6]];
total_days = data_list[[7]];
total_days_vector = c(1:total_days);
location =  data_list[[8]];

# Create copies of the temperature data for generations P, F1 and F2 if we're plotting generations separately.
if (plot_generations_separately) {
    temperature_data_frame_P = data.frame(temperature_data_frame);
    temperature_data_frame_F1 = data.frame(temperature_data_frame);
    temperature_data_frame_F2 = data.frame(temperature_data_frame);
}

# Get the ticks date labels for plots.
ticks_and_labels = get_x_axis_ticks_and_labels(temperature_data_frame, total_days, start_doy_ytd, end_doy_ytd);
ticks = c(unlist(ticks_and_labels[1]));
date_labels = c(unlist(ticks_and_labels[2]));
# All latitude values are the same, so get the value for plots from the first row.
latitude = temperature_data_frame$LATITUDE[1];

            process_total_adults = TRUE;
        }
    }
}
# Initialize matrices.
if (process_eggs) {
    Eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
}
if (process_young_nymphs | process_total_nymphs) {
    YoungNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);

    for (row in 1:total_days) {
        # Get the integer day of the year for the current row.
        doy = temperature_data_frame$DOY[row];
        # Photoperiod in the day.
        photoperiod = temperature_data_frame$DAYLEN[row];
        temp.profile = get_temperature_at_hour(latitude, temperature_data_frame, row, total_days);
        mean.temp = temp.profile[1];
        averages.temp = temp.profile[2];
        averages.day[row] = averages.temp;
        # Trash bin for death.
        death.vector = NULL;

    # Save the analyzed data for generation F2.
    file_path = paste("output_data_dir", "03_generation_F2.csv", sep="/");
    write.csv(temperature_data_frame_F2, file=file_path, row.names=F);
}

if (plot_generations_separately) {
    for (life_stage in life_stages) {
        if (life_stage == "Egg") {
            # Start PDF device driver.
            dev.new(width=20, height=30);

49:1b6864c5b50a

option_list <- list(
    make_option(c("--adult_mortality"), action="store", dest="adult_mortality", type="integer", help="Adjustment rate for adult mortality"),
    make_option(c("--adult_accumulation"), action="store", dest="adult_accumulation", type="integer", help="Adjustment of degree-days accumulation (old nymph->adult)"),
    make_option(c("--egg_mortality"), action="store", dest="egg_mortality", type="integer", help="Adjustment rate for egg mortality"),
    make_option(c("--end_date"), action="store", dest="end_date", default=NULL, help="End date for custom date interval"),
    make_option(c("--input_norm"), action="store", dest="input_norm", help="30 year normals temperature data for selected station"),
    make_option(c("--input_ytd"), action="store", dest="input_ytd", default=NULL, help="Year-to-date temperature data for selected location"),
    make_option(c("--insect"), action="store", dest="insect", help="Insect name"),
    make_option(c("--insects_per_replication"), action="store", dest="insects_per_replication", type="integer", help="Number of insects with which to start each replication"),
    make_option(c("--life_stages"), action="store", dest="life_stages", help="Selected life stages for plotting"),

    make_option(c("--oviposition"), action="store", dest="oviposition", type="integer", help="Adjustment for oviposition rate"),
    make_option(c("--photoperiod"), action="store", dest="photoperiod", type="double", help="Critical photoperiod for diapause induction/termination"),
    make_option(c("--plot_generations_separately"), action="store", dest="plot_generations_separately", help="Plot Plot P, F1 and F2 as separate lines or pool across them"),
    make_option(c("--plot_std_error"), action="store", dest="plot_std_error", help="Plot Standard error"),
    make_option(c("--replications"), action="store", dest="replications", type="integer", help="Number of replications"),
    make_option(c("--start_date"), action="store", dest="start_date", default=NULL, help="Start date for custom date interval"),
    make_option(c("--young_nymph_accumulation"), action="store", dest="young_nymph_accumulation", type="integer", help="Adjustment of degree-days accumulation (egg->young nymph)")
)

parser <- OptionParser(usage="%prog [options] file", option_list=option_list);
args <- parse_args(parser, positional_arguments=TRUE);
opt <- args$options;

add_daylight_length = function(temperature_data_frame) {
    # Return temperature_data_frame with an added column
    # of daylight length (photoperido profile).
    num_rows = dim(temperature_data_frame)[1];
    # From Forsythe 1995.
    p = 0.8333;
    latitude = temperature_data_frame$LATITUDE[1];
    daylight_length_vector = NULL;
    for (i in 1:num_rows) {
        # Get the day of the year from the current row

    # Append vector vec as a new column to data_frame.
    data_frame[,num_columns+1] = vec;
    # Reset the column names with the additional column for later access.
    colnames(data_frame) = append(current_column_names, new_column_name);
    return(data_frame);
}

extract_date_interval_rows = function(df, start_date, end_date) {
    date_interval_rows = df[df$DATE >= start_date & df$DATE <= end_date];
    return(date_interval_rows);
}

from_30_year_normals = function(norm_data_frame, start_date_doy, end_date_doy, year) {
    # The data we want is fully contained within the 30 year normals data.
    first_norm_row = which(norm_data_frame$DOY==start_date_doy);
    last_norm_row = which(norm_data_frame$DOY==end_date_doy);
    # Add 1 to the number of rows to ensure that the end date is included.
    tmp_data_frame_rows = last_norm_row - first_norm_row + 1;
    tmp_data_frame = get_new_temperature_data_frame(nrow=tmp_data_frame_rows);
    j = 0;
    for (i in first_norm_row:last_norm_row) {
        j = j + 1;
        tmp_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
    }
    return (tmp_data_frame);
}

get_file_path = function(life_stage, base_name, life_stage_nymph=NULL, life_stage_adult=NULL) {
    if (!is.null(life_stage_nymph)) {
        lsi = get_life_stage_index(life_stage, life_stage_nymph=life_stage_nymph);

    # F2 standard error.
    f2_se = apply(f2_replications, 1, sd) / sqrt(opt$replications);
    return(list(p_m, p_se, f1_m, f1_se, f2_m, f2_se))
}

get_new_norm_data_frame = function(is_leap_year, input_norm=NULL, nrow=0) {
    # The input_norm data has the following 10 columns:
    # STATIONID, LATITUDE, LONGITUDE, ELEV_M, NAME, ST, MMDD, DOY, TMIN, TMAX
    column_names = c("STATIONID", "LATITUDE","LONGITUDE", "ELEV_M", "NAME", "ST", "MMDD", "DOY", "TMIN", "TMAX");
    if (is.null(input_norm)) {
        norm_data_frame = data.frame(matrix(ncol=10, nrow));
        # Set the norm_data_frame column names for access.
        colnames(norm_data_frame) = column_names;
    } else {
        norm_data_frame = read.csv(file=input_norm, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
        # Set the norm_data_frame column names for access.
        colnames(norm_data_frame) = column_names;
        if (!is_leap_year) {
            # All normals data includes Feb 29 which is row 60 in
            # the data, so delete that row if we're not in a leap year.
            norm_data_frame = norm_data_frame[-c(60),];
            # Since we've removed row 60, we need to subtract 1 from
            # each value in the DOY column of the data frame starting
            # with the 60th row.
            num_rows = dim(norm_data_frame)[1];
            for (i in 60:num_rows) {
                leap_year_doy = norm_data_frame$DOY[i];
                non_leap_year_doy = leap_year_doy - 1;
                norm_data_frame$DOY[i] = non_leap_year_doy;
            }
        }
    }
    return (norm_data_frame);
}

get_new_temperature_data_frame = function(input_ytd=NULL, nrow=0) {
    # The input_ytd data has the following 6 columns:
    # LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
    if (is.null(input_ytd)) {
        temperature_data_frame = data.frame(matrix(ncol=6, nrow));
    } else {
        temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
    }
    colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
    return(temperature_data_frame);
}

get_next_normals_row = function(norm_data_frame, year, index) {
    # Return the next 30 year normals row formatted
    # appropriately for the year-to-date data.
    latitude = norm_data_frame[index,"LATITUDE"][1];
    longitude = norm_data_frame[index,"LONGITUDE"][1];
    # Format the date.
    mmdd = norm_data_frame[index,"MMDD"][1];
    date_str = paste(year, mmdd, sep="-");
    doy = norm_data_frame[index,"DOY"][1];
    tmin = norm_data_frame[index,"TMIN"][1];
    tmax = norm_data_frame[index,"TMAX"][1];
    return(list(latitude, longitude, date_str, doy, tmin, tmax));
}

get_temperature_at_hour = function(latitude, temperature_data_frame, row) {
    # Base development threshold for Brown Marmorated Stink Bug
    # insect phenology model.
    threshold = 14.17;
    # Minimum temperature for current row.
    curr_min_temp = temperature_data_frame$TMIN[row];

        averages = sum(dh) / 24;
    }
    return(c(curr_mean_temp, averages))
}

get_tick_index = function(index, last_tick, ticks, tick_labels, tick_sep) {
    # The R code tries hard not to draw overlapping tick labels, and so
    # will omit labels where they would abut or overlap previously drawn
    # labels. This can result in, for example, every other tick being
    # labelled.  We'll keep track of the last tick to make sure all of
    # the month labels are displayed, and missing ticks are restricted
    # to Sundays which have no labels anyway.
    if (last_tick==0) {
        return(length(ticks)+1);
    }
    last_saved_tick = ticks[[length(ticks)]];
    if (index-last_saved_tick<tick_sep) {
        last_saved_month = tick_labels[[length(tick_labels)]];
        if (last_saved_month=="") {
            # We're safe overwriting a tick
            # with no label (i.e., a Sunday tick).
            return(length(ticks));
        } else {

    } else {
        return(365);
    }
}

get_x_axis_ticks_and_labels = function(temperature_data_frame, prepend_end_doy_norm, append_start_doy_norm, date_interval) {
    # Generate a list of ticks and labels for plotting the x axis.
    if (prepend_end_doy_norm > 0) {
        prepend_end_norm_row = which(temperature_data_frame$DOY==prepend_end_doy_norm);
    } else {
        prepend_end_norm_row = 0;
    }
    if (append_start_doy_norm > 0) {
        append_start_norm_row = which(temperature_data_frame$DOY==append_start_doy_norm);
    } else {
        append_start_norm_row = 0;
    }
    num_rows = dim(temperature_data_frame)[1];
    tick_labels = list();
    ticks = list();
    current_month_label = NULL;
    last_tick = 0;
    if (date_interval) {
        tick_sep = 0;
    } else {
        tick_sep = 3;
    }
    for (i in 1:num_rows) {
        # Get the year and month from the date which
        # has the format YYYY-MM-DD.
        date = format(temperature_data_frame$DATE[i]);
        # Get the month label.
        items = strsplit(date, "-")[[1]];
        month = items[2];
        month_label = month.abb[as.integer(month)];
        day = as.integer(items[3]);
        doy = as.integer(temperature_data_frame$DOY[i]);
        # We're plotting the entire year, so ticks will
        # occur on Sundays and the first of each month.
        if (i == prepend_end_norm_row) {
            # Add a tick for the end of the 30 year normnals data
            # that was prepended to the year-to-date data.
            label_str = "End prepended 30 year normals";
            tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
            ticks[tick_index] = i;
            if (date_interval) {
                # Append the day to label_str
                tick_labels[tick_index] = paste(label_str, day, sep=" ");
            } else {
                tick_labels[tick_index] = label_str;
            }
            last_tick = i;
        } else if (doy == append_start_doy_norm) {
            # Add a tick for the start of the 30 year normnals data
            # that was appended to the year-to-date data.
            label_str = "Start appended 30 year normals";
            tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
            ticks[tick_index] = i;
            if (!identical(current_month_label, month_label)) {
                # Append the month to label_str.
                label_str = paste(label_str, month_label, spe=" ");
                current_month_label = month_label;
            }
            if (date_interval) {
                # Append the day to label_str
                label_str = paste(label_str, day, sep=" ");
            }
            tick_labels[tick_index] = label_str;
            last_tick = i;
        } else if (i==num_rows) {
            # Add a tick for the last day of the year.
            label_str = "";
            tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
            ticks[tick_index] = i;
            if (!identical(current_month_label, month_label)) {
                # Append the month to label_str.
                label_str = month_label;
                current_month_label = month_label;
            }
            if (date_interval) {
                # Append the day to label_str
                label_str = paste(label_str, day, sep=" ");
            }
            tick_labels[tick_index] = label_str;
        } else {
            if (!identical(current_month_label, month_label)) {
                # Add a tick for the month.
                tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
                ticks[tick_index] = i;
                if (date_interval) {
                    # Append the day to the month.
                    tick_labels[tick_index] = paste(month_label, day, sep=" ");
                } else {
                    tick_labels[tick_index] = month_label;
                }
                current_month_label = month_label;
                last_tick = i;
            }
            tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
            if (!is.null(tick_index)) {
                if (date_interval) {
                    # Add a tick for every day. The first tick is the
                    # month label, so add a tick only if i is not 1
                    if (i>1 & day>1) {
                        tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
                        ticks[tick_index] = i;
                        # Add the day as the label.
                        tick_labels[tick_index] = day;
                        last_tick = i;
                     }
                } else {
                    # Get the day.
                    day = weekdays(as.Date(date));
                    if (day=="Sunday") {
                        # Add a tick if we're on a Sunday.
                        ticks[tick_index] = i;
                        # Add a blank month label so it is not displayed.
                        tick_labels[tick_index] = "";
                        last_tick = i;
                    }
                }
            }
        }
    }
    return(list(ticks, tick_labels));
}

get_year_from_date = function(date_str) {
    date_str_items = strsplit(date_str, "-")[[1]];
    return (date_str_items[1]);
}

is_leap_year = function(date_str) {
    # Extract the year from the date_str.
    date = format(date_str);

        mortality.probability = temperature * 0.0008 + 0.03;
    }
    return(mortality.probability);
}

parse_input_data = function(input_ytd, input_norm, location, start_date, end_date) {
    # The end DOY for norm data prepended to ytd data.
    prepend_end_doy_norm = 0;
    # The start DOY for norm data appended to ytd data.
    append_start_doy_norm = 0;
    if (is.null(start_date) && is.null(end_date)) {
        # We're not dealing with a date interval.
        date_interval = FALSE;
        if (is.null(input_ytd)) {
            # Base all dates on the current date since 30 year
            # normals data does not include any dates.
            year = format(Sys.Date(), "%Y");
        }
    } else {
        date_interval = TRUE;
        year = get_year_from_date(start_date);
        # Get the DOY for start_date and end_date.
        start_date_doy = as.integer(strftime(start_date, format="%j"));
        end_date_doy = as.integer(strftime(end_date, format="%j"));
    }
    if (is.null(input_ytd)) {
        # We're processing only the 30 year normals data.
        processing_year_to_date_data = FALSE;
        if (is.null(start_date) && is.null(end_date)) {
            # We're processing the entire year, so we can
            # set the start_date to Jan 1.
            start_date = paste(year, "01", "01", sep="-");
        }
    } else {
        processing_year_to_date_data = TRUE;
        # Read the input_ytd temperature data file into a data frame.
        temperature_data_frame = get_new_temperature_data_frame(input_ytd=input_ytd);
        num_ytd_rows = dim(temperature_data_frame)[1];
        if (!date_interval) {
            start_date = temperature_data_frame$DATE[1];
            year = get_year_from_date(start_date);
        }
    }
    # See if we're in a leap year.
    is_leap_year = is_leap_year(start_date);
    # Read the input_norm temperature datafile into a data frame.
    norm_data_frame = get_new_norm_data_frame(is_leap_year, input_norm=input_norm);
    if (processing_year_to_date_data) {
        if (date_interval) {
            # We're plotting a date interval.
            start_date_ytd_row = which(temperature_data_frame$DATE==start_date);
            if (length(start_date_ytd_row) > 0) {
                # The start date is contained within the input_ytd data.
                start_date_ytd_row = start_date_ytd_row[1];
                start_doy_ytd = as.integer(temperature_data_frame$DOY[start_date_ytd_row]);
            } else {
                # The start date is contained within the input_norm data.
                start_date_ytd_row = 0;
                start_date_norm_row = which(norm_data_frame$DOY==start_date_doy);
            }
            end_date_ytd_row = which(temperature_data_frame$DATE==end_date);
            if (length(end_date_ytd_row) > 0) {
                end_date_ytd_row = end_date_ytd_row[1];
                # The end date is contained within the input_ytd data.
                end_doy_ytd = as.integer(temperature_data_frame$DOY[end_date_ytd_row]);
            } else {
                end_date_ytd_row = 0;
            }
        } else {
            # We're plotting an entire year.
            # Get the start date and end date from temperature_data_frame.
            start_date_ytd_row = 1;
            # Temporarily set start_date to get the year.
            start_date = temperature_data_frame$DATE[1];
            end_date_ytd_row = num_ytd_rows;
            end_date = temperature_data_frame$DATE[num_ytd_rows];
            date_str = format(start_date);
            # Extract the year from the start date.
            date_str_items = strsplit(date_str, "-")[[1]];
            # Get the year.
            year = date_str_items[1];
            # Properly set the start_date to be Jan 1 of the year.
            start_date = paste(year, "01", "01", sep="-");
            # Properly set the end_date to be Dec 31 of the year.
            end_date = paste(year, "12", "31", sep="-");
            # Save the first DOY to later check if start_date is Jan 1.
            start_doy_ytd = as.integer(temperature_data_frame$DOY[1]);
            end_doy_ytd = as.integer(temperature_data_frame$DOY[num_ytd_rows]);
        }
    } else {
        # We're processing only the 30 year normals data, so create an empty
        # data frame for containing temperature data after it is converted
        # from the 30 year normals format to the year-to-date format.
        temperature_data_frame = get_new_temperature_data_frame();
        if (date_interval) {
            # We're plotting a date interval.
            # Extract the year, month and day from the start date.
            start_date_str = format(start_date);
            start_date_str_items = strsplit(start_date_str, "-")[[1]];
            year = start_date_str_items[1];
            start_date_month = start_date_str_items[2];
            start_date_day = start_date_str_items[3];
            start_date = paste(year, start_date_month, start_date_day, sep="-");
            # Extract the month and day from the end date.
            end_date_str = format(start_date);
            end_date_str_items = strsplit(end_date_str, "-")[[1]];
            end_date_month = end_date_str_items[2];
            end_date_day = end_date_str_items[3];
            end_date = paste(year, end_date_month, end_date_day, sep="-");
        } else {
            # We're plotting an entire year.
            start_date = paste(year, "01", "01", sep="-");
            end_date = paste(year, "12", "31", sep="-");
        }
    }
    # Set the location to be the station name if the user elected not to enter it.
    if (is.null(location) | length(location) == 0) {
        location = norm_data_frame$NAME[1];
    }
    if (processing_year_to_date_data) {
        # Merge the year-to-date data with the 30 year normals data.
        if (date_interval) {
            # The values of start_date_ytd_row and end_date_ytd_row were set above.
            if (start_date_ytd_row > 0 & end_date_ytd_row > 0) {
                # The date interval is contained within the input_ytd
                # data, so we don't need to merge the 30 year normals data.
                temperature_data_frame = temperature_data_frame[start_date_ytd_row:end_date_ytd_row,];
            } else if (start_date_ytd_row == 0 & end_date_ytd_row > 0) {
                # The date interval starts in input_norm and ends in
                # input_ytd, so prepend appropriate rows from input_norm
                # to appropriate rows from input_ytd.
                first_norm_row = which(norm_data_frame$DOY==start_date_doy);
                # Get the first DOY from temperature_data_frame.
                first_ytd_doy = temperature_data_frame$DOY[1];
                # End DOY of input_norm data prepended to input_ytd.
                prepend_end_doy_norm = first_ytd_doy - 1;
                # Get the number of rows for the restricted date interval
                # that are contained in temperature_data_frame.
                num_temperature_data_frame_rows = end_date_ytd_row;
                # Get the last row needed from the 30 year normals data.
                last_norm_row = which(norm_data_frame$DOY==prepend_end_doy_norm);
                # Get the number of rows for the restricted date interval
                # that are contained in norm_data_frame.
                num_norm_data_frame_rows = last_norm_row - first_norm_row;
                # Create a temporary data frame to contain the 30 year normals
                # data from the start date to the date immediately prior to the
                # first row of the input_ytd data.
                tmp_norm_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
                j = 1;
                for (i in first_norm_row:last_norm_row) {
                    # Populate the temp_data_frame row with
                    # values from norm_data_frame.
                    tmp_norm_data_frame[j,] = get_next_normals_row(norm_data_frame, year, i);
                    j = j + 1;
                }
                # Create a second temporary data frame containing the
                # appropriate rows from temperature_data_frame.
                tmp_temperature_data_frame = temperature_data_frame[1:num_temperature_data_frame_rows,];
                # Merge the 2 temporary data frames.
                temperature_data_frame = rbind(tmp_norm_data_frame, tmp_temperature_data_frame);
            } else if (start_date_ytd_row > 0 & end_date_ytd_row == 0) {
                # The date interval starts in input_ytd and ends in input_norm,
                # so append appropriate rows from input_norm to appropriate rows
                # from input_ytd. First, get the number of rows for the restricted
                # date interval that are contained in temperature_data_frame.
                num_temperature_data_frame_rows = num_ytd_rows - start_date_ytd_row + 1;
                # Get the DOY of the last row in the input_ytd data.
                last_ytd_doy = temperature_data_frame$DOY[num_ytd_rows];
                # Get the DOYs for the first and last rows from norm_data_frame
                # that will be appended to temperature_data_frame.
                append_start_doy_norm = last_ytd_doy + 1;
                # Get the row from norm_data_frame containing first_norm_doy.
                first_norm_row = which(norm_data_frame$DOY == append_start_doy_norm);
                # Get the row from norm_data_frame containing end_date_doy.
                last_norm_row = which(norm_data_frame$DOY == end_date_doy);
                # Get the number of rows for the restricted date interval
                # that are contained in norm_data_frame.
                num_norm_data_frame_rows = last_norm_row - first_norm_row;
                # Create a temporary data frame to contain the data
                # taken from both temperature_data_frame and norm_data_frame
                # for the date interval.
                tmp_data_frame = get_new_temperature_data_frame(nrow=num_temperature_data_frame_rows+num_norm_data_frame_rows);
                # Populate tmp_data_frame with the appropriate rows from temperature_data_frame.
                j = start_date_ytd_row;
                for (i in 1:num_temperature_data_frame_rows) {
                    tmp_data_frame[i,] = temperature_data_frame[j,];
                    j = j + 1;
                }
                # Apppend the appropriate rows from norm_data_frame to tmp_data_frame.
                current_iteration = num_temperature_data_frame_rows + 1;
                num_iterations = current_iteration + num_norm_data_frame_rows;
                j = first_norm_row;
                for (i in current_iteration:num_iterations) {
                    tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, j);
                    j = j + 1;
                }
                temperature_data_frame = tmp_data_frame[,];
            } else if (start_date_ytd_row == 0 & end_date_ytd_row == 0) {
                # The date interval is contained witin input_norm.
                temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
            }
        } else {
            # We're plotting an entire year.
            if (start_doy_ytd > 1) {
                # The input_ytd data starts after Jan 1, so prepend
                # appropriate rows from input_norm to temperature_data_frame.
                prepend_end_doy_norm = start_doy_ytd - 1;
                last_norm_row = which(norm_data_frame$DOY == prepend_end_doy_norm);
                # Create a temporary data frame to contain the input_norm data
                # from Jan 1 to the date immediately prior to start_date.
                tmp_data_frame = temperature_data_frame[FALSE,];
                # Populate tmp_data_frame with appropriate rows from norm_data_frame.
                for (i in 1:last_norm_row) {
                    tmp_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
                }
                # Merge the temporary data frame with temperature_data_frame.
                temperature_data_frame = rbind(tmp_data_frame, temperature_data_frame);
            }
            # Set the value of total_days.
            total_days = get_total_days(is_leap_year);
            if (end_doy_ytd < total_days) {
                # Define the next row for the year-to-date data from the 30 year normals data.
                append_start_doy_norm = end_doy_ytd + 1;
                first_norm_row = which(norm_data_frame$DOY == append_start_doy_norm);
                # Append the 30 year normals data to the year-to-date data.
                for (i in first_norm_row:total_days) {
                    temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
                }
            }
        }
    } else {
        # We're processing only the 30 year normals data.
        if (date_interval) {
            # Populate temperature_data_frame from norm_data_frame.
            temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
        } else {
            total_days = get_total_days(is_leap_year);
            for (i in 1:total_days) {
                temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
            }
        }
    }
    # Add a column containing the daylight length for each day.
    temperature_data_frame = add_daylight_length(temperature_data_frame);
    return(list(temperature_data_frame, start_date, end_date, prepend_end_doy_norm, append_start_doy_norm, is_leap_year, location));
}

render_chart = function(ticks, date_labels, chart_type, plot_std_error, insect, location, latitude, start_date, end_date, days, maxval,
    replications, life_stage, group, group_std_error, group2=NULL, group2_std_error=NULL, group3=NULL, group3_std_error=NULL,
    life_stages_adult=NULL, life_stages_nymph=NULL) {

            lines(days, group3-group3_std_error, col=4, lty=2);
        }
    }
}

stop_err = function(msg) {
    cat(msg, file=stderr());
    quit(save="no", status=1);
}

validate_date = function(date_str) {
    valid_date = as.Date(date_str, format="%Y-%m-%d");
    if( class(valid_date)=="try-error" || is.na(valid_date)) {
        msg = paste("Invalid date: ", date_str, ", valid date format is yyyy-mm-dd.", sep="");
        stop_err(msg);
    }
    return(valid_date);
}

if (is.null(opt$input_ytd)) {
    processing_year_to_date_data = FALSE;
} else {
    processing_year_to_date_data = TRUE;
}
# Determine if we're plotting generations separately.
if (opt$plot_generations_separately=="yes") {
    plot_generations_separately = TRUE;
} else {
    plot_generations_separately = FALSE;
}
# Parse the inputs.
data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$location, opt$start_date, opt$end_date);
temperature_data_frame = data_list[[1]];
# Information needed for plots, some of these values are
# being reset here since in some case they were set above.
start_date = data_list[[2]];
end_date = data_list[[3]];
prepend_end_doy_norm = data_list[[4]];
append_start_doy_norm = data_list[[5]];
is_leap_year = data_list[[6]];
location = data_list[[7]];

if (is.null(opt$start_date) && is.null(opt$end_date)) {
    # We're plotting an entire year.
    date_interval = FALSE;
    # Display the total number of days in the Galaxy history item blurb.
    if (processing_year_to_date_data) {
        cat("Number of days year-to-date: ", opt$num_days_ytd, "\n");
    } else {
        if (is_leap_year) {
            num_days = 366;
        } else {
            num_days = 365;
        }
        cat("Number of days in year: ", num_days, "\n");
    }
} else {
    # FIXME: currently custom date fields are free text, but
    # Galaxy should soon include support for a date selector
    # at which point this tool should be enhanced to use it.
    # Validate start_date.
    date_interval = TRUE;
    # Calaculate the number of days in the date interval rather
    # than using the number of rows in the input temperature data.
    start_date = validate_date(opt$start_date);
    # Validate end_date.
    end_date = validate_date(opt$end_date);
    if (start_date >= end_date) {
        stop_err("The start date must be between 1 and 50 days before the end date when setting date intervals for plots.");
    }
    # Calculate the number of days in the date interval.
    num_days = difftime(end_date, start_date, units=c("days"));
    # Add 1 to the number of days to make the dates inclusive.  For
    # example, if the user enters a date range of 2018-01-01 to
    # 2018-01-31, they likely expect the end date to be included.
    num_days = num_days + 1;
    if (num_days > 50) {
        # We need to restrict date intervals since
        # plots render tick marks for each day.
        stop_err("Date intervals for plotting cannot exceed 50 days.");
    }
    # Display the total number of days in the Galaxy history item blurb.
    cat("Number of days in date interval: ", num_days, "\n");
}
# Create copies of the temperature data for generations P, F1 and F2 if we're plotting generations separately.
if (plot_generations_separately) {
    temperature_data_frame_P = data.frame(temperature_data_frame);
    temperature_data_frame_F1 = data.frame(temperature_data_frame);
    temperature_data_frame_F2 = data.frame(temperature_data_frame);
}

# Get the ticks date labels for plots.
ticks_and_labels = get_x_axis_ticks_and_labels(temperature_data_frame, prepend_end_doy_norm, append_start_doy_norm, date_interval);
ticks = c(unlist(ticks_and_labels[1]));
date_labels = c(unlist(ticks_and_labels[2]));
# All latitude values are the same, so get the value for plots from the first row.
latitude = temperature_data_frame$LATITUDE[1];

            process_total_adults = TRUE;
        }
    }
}
# Initialize matrices.
total_days = dim(temperature_data_frame)[1];
if (process_eggs) {
    Eggs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);
}
if (process_young_nymphs | process_total_nymphs) {
    YoungNymphs.replications = matrix(rep(0, total_days*opt$replications), ncol=opt$replications);

    for (row in 1:total_days) {
        # Get the integer day of the year for the current row.
        doy = temperature_data_frame$DOY[row];
        # Photoperiod in the day.
        photoperiod = temperature_data_frame$DAYLEN[row];
        temp.profile = get_temperature_at_hour(latitude, temperature_data_frame, row);
        mean.temp = temp.profile[1];
        averages.temp = temp.profile[2];
        averages.day[row] = averages.temp;
        # Trash bin for death.
        death.vector = NULL;

    # Save the analyzed data for generation F2.
    file_path = paste("output_data_dir", "03_generation_F2.csv", sep="/");
    write.csv(temperature_data_frame_F2, file=file_path, row.names=F);
}

total_days_vector = c(1:dim(temperature_data_frame)[1]);
if (plot_generations_separately) {
    for (life_stage in life_stages) {
        if (life_stage == "Egg") {
            # Start PDF device driver.
            dev.new(width=20, height=30);