stacomiR (version 0.6.1)

report_mig_char-class: Migration report along with quantitative and qualitative characteristics

Description

Migration along with qualitative or quantitative characteristics or both (e.g.) weight of eels according to the size class per period of time, weight of fish according to gender, number of fish per age class. This class does not split migration evenly over time period. So, unlike calculations made in class report_mig and report_mig_mult the whole time span of the migration operation is not considered, only the date of beginning of the operation is used to perform calculations.

Slots

calcdata

A 'list' of calculated data, filled in by the calcule method

data

A data.frame inherited from report_sample_char-class

dc

An object of class ref_dc-class inherited from report_sample_char-class

taxa

An object of class ref_taxa-class inherited from report_sample_char-class

stage

An object of class ref_stage-class inherited from report_sample_char-class

horodatedebut

An object of class ref_horodate-class inherited from report_sample_char-class

horodatefin

An object of class ref_horodate-class inherited from report_sample_char-class

par

An object of class ref_par-class inherited from report_sample_char-class

echantillon

An object of class ref_choice-class, vector of choice

parquan

An object of class ref_parquan-class, quantitative parameter

parqual

An object of class ref_parqual-class, qualitative parameter

Objects from the Class

Objects can be created by calls of the form new('report_mig_char', ...). they are loaded by the interface using interface_report_mig_char function.

Author

Cedric Briand

See Also

Other report Objects: report_annual-class, report_dc-class, report_df-class, report_env-class, report_ge_weight-class, report_mig-class, report_mig_env-class, report_mig_interannual-class, report_mig_mult-class, report_sample_char-class, report_sea_age-class, report_silver_eel-class, report_species-class

Examples

require(stacomiR)

stacomi(
	database_expected=FALSE, sch='logrami')
# this requires a database with the schema logrami
# prompt for user and password but you can set appropriate options for host, port and dbname
if (FALSE) {
	stacomi(database_expected=TRUE, sch='logrami')	
	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						
	)	
  r_mig_char <- new("report_mig_char")
  # here parqual is not in the list
  # so this is equivalent to parqual=NULL
  # default for echantillon is "with"
  r_mig_char <- choice_c(r_mig_char,
	  dc=c(107,108,101),
	  taxa=c("Salmo salar"),
	  stage=c('5','11','BEC','BER','IND'),
	  parquan=c('C001','1786','1785'),
	  horodatedebut="2012-01-01",
	  horodatefin="2012-12-31",
	  silent=FALSE)
  # r_mig_char<-charge(r_mig_char) not necessary there
  r_mig_char <- connect(r_mig_char)
  
}	
# load the dataset generated by previous lines
data("r_mig_char")

r_mig_char<-calcule(r_mig_char, silent=TRUE)
plot(r_mig_char,plot.type="quant", silent=TRUE)
# one quantitative parameter found, manual choice of color
plot(r_mig_char,plot.type="quant",color_parm=c("C001"="red"), silent=TRUE)
# age will be plotted as a qualitative variable
# here we split size data accoding to the limit known between different ages from
# scale reading in the Loire
r_mig_char <- setasqualitative(r_mig_char,par='C001',
		breaks=c(0,675,850,2000),
		labels=c("age 1","age 2","age 3"))
r_mig_char<-calcule(r_mig_char, silent=TRUE)
plot(r_mig_char, plot.type="qual", silent=TRUE)
plot(r_mig_char, plot.type="crossed")
plot(r_mig_char, plot.type="crossed",
    color_parm=c("age 1"="#379ec6","age 2"="#173957","age 3"="#b09953"))
xt<-xtable(r_mig_char)
# use method print.xtable to get the output