insect_phenology_model: insect_phenology

comparison insect_phenology_model.R @ 49:1b6864c5b50a draft

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author	greg
date	Tue, 05 Jun 2018 07:52:59 -0400
parents	58a823b1d940
children	927321ed0322

comparison

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-:99e1c1300fcd
+: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$options;
-add_daylight_length = function(temperature_data_frame, num_rows) {
+add_daylight_length = function(temperature_data_frame) {
-# Return a vector of daylight length (photoperido profile) for
+# Return temperature_data_frame with an added column
-# the number of days specified in the input_ytd temperature data
+# of daylight length (photoperido profile).
-# (from Forsythe 1995).
+num_rows = dim(temperature_data_frame)[1];
+# From Forsythe 1995.
 p = 0.8333;
 latitude = temperature_data_frame$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$replications);
 return(list(p_m, p_se, f1_m, f1_se, f2_m, f2_se))
 }
-get_next_normals_row = function(norm_data_frame, year, is_leap_year, index) {
+get_new_norm_data_frame = function(is_leap_year, input_norm=NULL, nrow=0) {
+# The input_norm data has the following 10 columns:
+# STATIONID, LATITUDE, LONGITUDE, ELEV_M, NAME, ST, MMDD, DOY, TMIN, TMAX
+column_names = c("STATIONID", "LATITUDE","LONGITUDE", "ELEV_M", "NAME", "ST", "MMDD", "DOY", "TMIN", "TMAX");
+if (is.null(input_norm)) {
+norm_data_frame = data.frame(matrix(ncol=10, nrow));
+# Set the norm_data_frame column names for access.
+colnames(norm_data_frame) = column_names;
+} else {
+norm_data_frame = read.csv(file=input_norm, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
+# Set the norm_data_frame column names for access.
+colnames(norm_data_frame) = column_names;
+if (!is_leap_year) {
+# All normals data includes Feb 29 which is row 60 in
+# the data, so delete that row if we're not in a leap year.
+norm_data_frame = norm_data_frame[-c(60),];
+# Since we've removed row 60, we need to subtract 1 from
+# each value in the DOY column of the data frame starting
+# with the 60th row.
+num_rows = dim(norm_data_frame)[1];
+for (i in 60:num_rows) {
+leap_year_doy = norm_data_frame$DOY[i];
+non_leap_year_doy = leap_year_doy - 1;
+norm_data_frame$DOY[i] = non_leap_year_doy;
+}
+}
+}
+return (norm_data_frame);
+}
+get_new_temperature_data_frame = function(input_ytd=NULL, nrow=0) {
+# The input_ytd data has the following 6 columns:
+# LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
+if (is.null(input_ytd)) {
+temperature_data_frame = data.frame(matrix(ncol=6, nrow));
+} else {
+temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
+}
+colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
+return(temperature_data_frame);
+}
+get_next_normals_row = function(norm_data_frame, year, index) {
 # Return the next 30 year normals row formatted
 # appropriately for the year-to-date data.
 latitude = norm_data_frame[index,"LATITUDE"][1];
 longitude = norm_data_frame[index,"LONGITUDE"][1];
 # Format the date.
 mmdd = norm_data_frame[index,"MMDD"][1];
 date_str = paste(year, mmdd, sep="-");
 doy = norm_data_frame[index,"DOY"][1];
-if (!is_leap_year) {
-# Since all normals data includes Feb 29, we have to
-# subtract 1 from DOY if we're not in a leap year since
-# we removed the Feb 29 row from the data frame above.
-doy = as.integer(doy) - 1;
-}
 tmin = norm_data_frame[index,"TMIN"][1];
 tmax = norm_data_frame[index,"TMAX"][1];
 return(list(latitude, longitude, date_str, doy, tmin, tmax));
 }
-get_temperature_at_hour = function(latitude, temperature_data_frame, row, num_days) {
+get_temperature_at_hour = function(latitude, temperature_data_frame, row) {
 # Base development threshold for Brown Marmorated Stink Bug
 # insect phenology model.
 threshold = 14.17;
 # Minimum temperature for current row.
 curr_min_temp = temperature_data_frame$TMIN[row];
 averages = sum(dh) / 24;
 }
 return(c(curr_mean_temp, averages))
 }
-get_tick_index = function(index, last_tick, ticks, month_labels) {
+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<3) {
+if (index-last_saved_tick<tick_sep) {
-last_saved_month = month_labels[[length(month_labels)]];
+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, num_rows, start_doy_ytd, end_doy_ytd) {
+get_x_axis_ticks_and_labels = function(temperature_data_frame, prepend_end_doy_norm, append_start_doy_norm, date_interval) {
-# Keep track of the years to see if spanning years.
+# Generate a list of ticks and labels for plotting the x axis.
-month_labels = list();
+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) {
-if (start_doy_ytd > 1 & i==start_doy_ytd-1) {
+# 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.
-tick_index = get_tick_index(i, last_tick, ticks, month_labels)
+label_str = "End prepended 30 year normals";
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
 ticks[tick_index] = i;
-month_labels[tick_index] = "End prepended 30 year normals";
+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 (end_doy_ytd > 0 & i==end_doy_ytd+1) {
+} 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.
-tick_index = get_tick_index(i, last_tick, ticks, month_labels)
+label_str = "Start appended 30 year normals";
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
 ticks[tick_index] = i;
-month_labels[tick_index] = "Start appended 30 year normals";
+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.
-tick_index = get_tick_index(i, last_tick, ticks, month_labels)
+label_str = "";
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
 ticks[tick_index] = i;
-month_labels[tick_index] = "";
+if (!identical(current_month_label, month_label)) {
-last_tick = i;
+# 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 {
-# 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.
+# Add a tick for the month.
-tick_index = get_tick_index(i, last_tick, ticks, month_labels)
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
 ticks[tick_index] = i;
-month_labels[tick_index] = month_label;
+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, month_labels)
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
 if (!is.null(tick_index)) {
-# Get the day.
+if (date_interval) {
-day = weekdays(as.Date(date));
+# Add a tick for every day. The first tick is the
-if (day=="Sunday") {
+# month label, so add a tick only if i is not 1
-# Add an x-axis tick if we're on a Sunday.
+if (i>1 & day>1) {
-ticks[tick_index] = i;
+tick_index = get_tick_index(i, last_tick, ticks, tick_labels, tick_sep)
-# Add a blank month label so it is not displayed.
+ticks[tick_index] = i;
-month_labels[tick_index] = "";
+# Add the day as the label.
-last_tick = i;
+tick_labels[tick_index] = day;
-}
+last_tick = i;
 }
-}
+} else {
-}
+# Get the day.
-return(list(ticks, month_labels));
+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, num_days_ytd, location) {
+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 analysing only the 30 year normals data, so create an empty
+# 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$DOY[num_ytd_rows]);
+}
+} else {
+# We're processing only the 30 year normals data, so create an empty
 # data frame for containing temperature data after it is converted
 # from the 30 year normals format to the year-to-date format.
-temperature_data_frame = data.frame(matrix(ncol=6, nrow=0));
+temperature_data_frame = get_new_temperature_data_frame();
-colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
+if (date_interval) {
-# Base all dates on the current date since 30 year
+# We're plotting a date interval.
-# normals data does not include any dates.
+# Extract the year, month and day from the start date.
-year = format(Sys.Date(), "%Y");
+start_date_str = format(start_date);
-start_date = paste(year, "01", "01", sep="-");
+start_date_str_items = strsplit(start_date_str, "-")[[1]];
-end_date = paste(year, "12", "31", sep="-");
+year = start_date_str_items[1];
-# Set invalid start and end DOY.
+start_date_month = start_date_str_items[2];
-start_doy_ytd = 0;
+start_date_day = start_date_str_items[3];
-end_doy_ytd = 0;
+start_date = paste(year, start_date_month, start_date_day, sep="-");
+# Extract the month and day from the end date.
+end_date_str = format(start_date);
+end_date_str_items = strsplit(end_date_str, "-")[[1]];
+end_date_month = end_date_str_items[2];
+end_date_day = end_date_str_items[3];
+end_date = paste(year, end_date_month, end_date_day, sep="-");
+} else {
+# We're plotting an entire year.
+start_date = paste(year, "01", "01", sep="-");
+end_date = paste(year, "12", "31", sep="-");
+}
+}
+# Set the location to be the station name if the user elected not to enter it.
+if (is.null(location) | length(location) == 0) {
+location = norm_data_frame$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 {
-# Read the input_ytd temperature datafile into a data frame.
+# We're processing only the 30 year normals data.
-# The input_ytd data has the following 6 columns:
+if (date_interval) {
-# LATITUDE, LONGITUDE, DATE, DOY, TMIN, TMAX
+# Populate temperature_data_frame from norm_data_frame.
-temperature_data_frame = read.csv(file=input_ytd, header=T, strip.white=TRUE, stringsAsFactors=FALSE, sep=",");
+temperature_data_frame = from_30_year_normals(norm_data_frame, start_date_doy, end_date_doy, year);
-# Set the temperature_data_frame column names for access.
+} else {
-colnames(temperature_data_frame) = c("LATITUDE", "LONGITUDE", "DATE", "DOY", "TMIN", "TMAX");
+total_days = get_total_days(is_leap_year);
-# Get the start date.
+for (i in 1:total_days) {
-start_date = temperature_data_frame$DATE[1];
+temperature_data_frame[i,] = get_next_normals_row(norm_data_frame, year, i);
-end_date = temperature_data_frame$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);
+temperature_data_frame = add_daylight_length(temperature_data_frame);
-return(list(temperature_data_frame, start_date, end_date, start_doy_ytd, end_doy_ytd, is_leap_year, total_days, location));
+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$plot_generations_separately=="yes") {
 plot_generations_separately = TRUE;
 } else {
 plot_generations_separately = FALSE;
 }
-# Display the total number of days in the Galaxy history item blurb.
-cat("Year-to-date number of days: ", opt$num_days_ytd, "\n");
 # Parse the inputs.
-data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$num_days_ytd, opt$location);
+data_list = parse_input_data(opt$input_ytd, opt$input_norm, opt$location, opt$start_date, opt$end_date);
 temperature_data_frame = data_list[[1]];
-# Information needed for plots.
+# Information needed for plots, some of these values are
+# being reset here since in some case they were set above.
 start_date = data_list[[2]];
 end_date = data_list[[3]];
-start_doy_ytd = data_list[[4]];
+prepend_end_doy_norm = data_list[[4]];
-end_doy_ytd = data_list[[5]];
+append_start_doy_norm = data_list[[5]];
 is_leap_year = data_list[[6]];
-total_days = data_list[[7]];
+location = data_list[[7]];
-total_days_vector = c(1:total_days);
-location =  data_list[[8]];
+if (is.null(opt$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, total_days, start_doy_ytd, end_doy_ytd);
+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, total_days);
+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);

Mercurial > repos > greg > insect_phenology_model

comparison insect_phenology_model.R @ 49:1b6864c5b50a draft