# complete documentation for this script can be found at :
# http://ucsb.piscoweb.org/~cburt/intertidal/workflow.html
classes = c(
 	'factor',		#site_code
 	'factor',		#survey_rep
 	'integer',	#year
 	'integer',	#month
 	'integer',	#day
 	'factor',		#section
 	'numeric',	#transect
 	'factor',		#location
	'factor',		#classification_code
 	'factor',		#sampler_code
 	'numeric',	#size
)
swath_data	= read.csv(
	file="swath_numeric.csv", 
	na.strings='.', 
	head=TRUE, 
	sep=",", 
	colClasses = classes
)
sites = unique(swath_data$site_code);
class_codes = unique(swath_data$class_code)
data = data.frame()
for(site in sites){
	data_for_site = subset(swath_data, site_code == sites[site]);
	years = unique(data_for_site$year)
	for(y in years){
		data_for_year = subset(data_for_site, year == y)
		t = table(data_for_year[c('transect', 'class_code')])
		mean = colMeans(t)
		standard_deviation = sd(t)
		n = length(t[, 1])
		standard_error = standard_deviation / sqrt(n)
		df = data.frame(
			year = y,
			site_code = sites[site],
			class_code=as.array(labels(mean)),
			mean=mean,
			standard_deviation=standard_deviation,
			standard_error=standard_error,
			n = n
		)
		data = rbind(data, df)
	}
}
write.table(
	data,
	file="./swath_output.csv",
	row.names=FALSE,
	col.names = FALSE,
	sep="\t",
	quote=FALSE
)