report_sample_char-class | R Documentation |
The report_sample_char class is used to load and display sample characteristics, which can be either continuous or discrete variable, for instance, it can be used to analyze size or sex structure during a given period.
data
A data frame
dc
An object of class ref_dc-class: the control devices
taxa
An object of class ref_taxa-class: the species
stage
An object of class ref_stage-class : the stages of the fish
par
An object of class ref_par-class: the parameters used
horodatedebut
An object of class ref_horodate-class
horodatefin
An object of class ref_horodate-class
Objects can be created by calls of the form
new('report_sample_char', ...)
This class is displayed by interface_report_sample_char, in the database, the class calls the content of the view vue_lot_ope_car
Cedric Briand cedric.briand@eptb-vilaine.fr
Other report Objects:
report_annual-class
,
report_dc-class
,
report_df-class
,
report_env-class
,
report_ge_weight-class
,
report_mig-class
,
report_mig_char-class
,
report_mig_env-class
,
report_mig_interannual-class
,
report_mig_mult-class
,
report_sea_age-class
,
report_silver_eel-class
,
report_species-class
# launching stacomi without connection to the database stacomi( database_expected=FALSE) # If you have a working database # the following line of code will create the r_sample_char # dataset from the iav (default) schema in the database ## Not run: stacomi(database_expected=TRUE) # uses 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_sample_char <- new("report_sample_char") # the following will load data for size, # parameters 1786 (total size) C001 (size at video control) # dc 5 and 6 are fishways located on the Arzal dam # two stages are selected r_sample_char <- choice_c(r_sample_char, dc=c(5,6), taxa=c("Anguilla anguilla"), stage=c("AGJ","CIV"), par=c(1785,1786,1787,"C001"), horodatedebut="2013-01-01", horodatefin="2013-12-31", silent=FALSE) # two warning produced, ignored if silent=TRUE r_sample_char <- connect(r_sample_char) r_sample_char <- calcule(r_sample_char,silent=TRUE) ## End(Not run) # load the dataset generated by previous lines data("r_sample_char") # A "violin" plot plot(r_sample_char,plot.type="1",silent=TRUE) # get the plot from envir_stacomi to change labels for name # if you use require(ggplot2) the :: argument is not needed # e.g. write require(ggplot2);g<-get("g",envir=envir_stacomi) # g+xlab("size")+ylab("year") if (requireNamespace("ggplot2", quietly = TRUE)){ g<-get("g",envir=envir_stacomi) g+ggplot2::xlab("size")+ggplot2::ylab("year") } # A boxplot per month plot(r_sample_char,plot.type="2",silent=TRUE) # A xyplot plot(r_sample_char,plot.type="3",silent=TRUE) ## Not run: ##################################### # an example graph created manually from data ##################################### # two variables one on DC, one on stage # passing dc information to the stage variable r_sample_char@data$std_libelle[r_sample_char@data$ope_dic_identifiant==5]<- "Yellow eel (vert. slot fishway)" r_sample_char@data$std_libelle[r_sample_char@data$std_libelle=="Anguille jaune"]<- "Yellow eel (ramp)" r_sample_char@data$std_libelle[r_sample_char@data$std_libelle=="civelle"]<- "Glass eel (ramp)" # creating a boxplot with custom output : an example # again if you use require(ggplot2) the :: argument is not needed if (requireNamespace("ggplot2", quietly = TRUE)){ g<-ggplot2::ggplot(r_sample_char@data)+ ggplot2::geom_boxplot(ggplot2::aes(x=annee, y =car_valeur_quantitatif, fill = std_libelle))+ ggplot2::xlab("size")+ggplot2::ylab("year")+ ggplot2::scale_fill_manual("stage & fishway", values=c("Yellow eel (vert. slot fishway)"="blue", "Yellow eel (ramp)"="turquoise3", "Glass eel (ramp)"="Cyan"))+ ggplot2::theme_bw() print(g) } # get a simple summary using Hmisc::describe summary(r_sample_char) # get the command line to create the object using choice_c # when the graphical interface has been used print(r_sample_char) ## End(Not run)
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