inst/examples/report_sea_age-example.R

In stacomiR: Fish Migration Monitoring

require(stacomiR)
stacomi(
	database_expected=FALSE)
# If you have a working database
# the following line of code will create the r_seaa dataset 
# from the logrami schema in the database
\dontrun{
		stacomi(database_expected=TRUE, sch='logrami')	
		# overrides the default option sch = 'iav'
		# prompt for user and password, you can set these in the options,
	  # including dbname and host
		if (interactive()){
			if (!exists("user")){
				user <- readline(prompt="Enter user: ")
				password <- readline(prompt="Enter password: ")	
			}	
		}
		options(					
				stacomiR.dbname = "bd_contmig_nat",
				stacomiR.host ="localhost",
				stacomiR.port = "5432",
				stacomiR.user = user,
				stacomiR.user = password						
		)	
  #create an instance of the class
  r_seaa<-new("report_sea_age")
  r_seaa<-choice_c(r_seaa,
	  dc=c(107,108,101),			
	  horodatedebut="2012-01-01",
	  horodatefin="2012-12-31",
	  limit1hm=675,
	  limit2hm=875,
	  silent=FALSE
  )
  r_seaa<-connect(r_seaa)
  r_seaa<-calcule(r_seaa)
  
}	
# load the dataset generated by previous lines
# Salmons from the loire on two dams
data("r_seaa")
# the calculation will fill the slot calcdata

# stages are in r_seaa@calcdata[["6"]][,"stage"] 
#look at data structure using str(r_seaa@calcdata[["6"]])

# plot data to confirm the split by limits is correct
plot(r_seaa, plot.type=1)

# if there are several dc, data it split by dc
plot(r_seaa, plot.type=2)
\dontrun{
# print a summary statistic, and save the output in a list for later use
  stats<-summary(r_seaa)
  
  
  write_database(r_seaa)
}