[Stacomir-commits] r331 - in pkg/stacomir: R inst/examples man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Sat Apr 1 14:56:35 CEST 2017
Author: briand
Date: 2017-04-01 14:56:34 +0200 (Sat, 01 Apr 2017)
New Revision: 331
Added:
pkg/stacomir/man/model-Bilan_poids_moyen-method.Rd.tex
Modified:
pkg/stacomir/R/BilanAnnuels.r
pkg/stacomir/R/BilanMigration.r
pkg/stacomir/R/Bilan_poids_moyen.r
pkg/stacomir/R/RefCoe.r
pkg/stacomir/inst/examples/bilanAnnuels_example.R
pkg/stacomir/inst/examples/bilan_poids_moyen_example.R
pkg/stacomir/man/BilanAnnuels-class.Rd
pkg/stacomir/man/Bilan_poids_moyen-class.Rd
pkg/stacomir/man/bMM_Arzal.Rd
pkg/stacomir/man/bM_Arzal.Rd
pkg/stacomir/man/b_carlot.Rd
pkg/stacomir/man/bfDC.Rd
pkg/stacomir/man/bfDF.Rd
pkg/stacomir/man/bilA.Rd
pkg/stacomir/man/bilanFonctionnementDC.Rd
pkg/stacomir/man/bilanFonctionnementDF.Rd
pkg/stacomir/man/bilanOperation.Rd
pkg/stacomir/man/bmi.Rd
Log:
Modified: pkg/stacomir/R/BilanAnnuels.r
===================================================================
--- pkg/stacomir/R/BilanAnnuels.r 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/R/BilanAnnuels.r 2017-04-01 12:56:34 UTC (rev 331)
@@ -483,7 +483,8 @@
} else if (length(lestax)==1 & length(lesstd)==1){
- g<-ggplot(dat,aes(x=annee,y=effectif))+geom_point(aes(col=dc))+
+ g<-ggplot(dat,aes(x=annee,y=effectif))+
+ geom_point(aes(col=dc))+
geom_line(aes(col=dc))+
theme_bw()
print(g)
Modified: pkg/stacomir/R/BilanMigration.r
===================================================================
--- pkg/stacomir/R/BilanMigration.r 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/R/BilanMigration.r 2017-04-01 12:56:34 UTC (rev 331)
@@ -592,26 +592,41 @@
data=data[data$Effectif_total!=0,]
jour_dans_lannee_non_nuls=data$debut_pas
col_a_retirer=match(c("No.pas","type_de_quantite","debut_pas","fin_pas"),colnames(data))
+ col_a_retirer=col_a_retirer[!is.na(col_a_retirer)] # car dans le cas des civelles et poids
+ # les colonnes ne sont pas les mêmes
data=data[,-col_a_retirer]
+ # below again the taux_d_echappement not there if glass eel and weights
+ if (is.null(data$taux_d_echappement)) data$taux_d_echappement<-NA
data$taux_d_echappement[data$taux_d_echappement==-1]<-NA
- # bug 27/02/2017 for some reasons crashes with arzal and coef_valeur_coefficient
- # and didn't crash for logrami or smatah
if (!is.null(data$coe_valeur_coefficient)){
data$coe_valeur_coefficient[data$"coe_valeur_coefficient"==1]<-NA
}else {data$coe_valeur_coefficient<-NA}
- peuventpaszero=match(c("taux_d_echappement","coe_valeur_coefficient"),colnames(data))
- data[,-peuventpaszero][data[,-peuventpaszero]==0]<-NA
+ cannotbenull=match(c("taux_d_echappement","coe_valeur_coefficient"),colnames(data))
+ data[,-cannotbenull][data[,-cannotbenull]==0]<-NA
annee<-as.numeric(unique(strftime(as.POSIXlt(bilanMigration at time.sequence),"%Y"))[1])
- aat_bilanmigrationjournalier_bjo=cbind(
- bilanMigration at dc@dc_selectionne,
- bilanMigration at taxons@data$tax_code,
- bilanMigration at stades@data$std_code,
- annee, # une valeur
- rep(jour_dans_lannee_non_nuls,ncol(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","taux_d_echappement","coe_valeur_coefficient")])),
- utils::stack(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","taux_d_echappement","coe_valeur_coefficient")]),
- Sys.time(),
- substr(toupper(get("sch",envir=envir_stacomi)),1,nchar(toupper(get("sch",envir=envir_stacomi)))-1)
- )
+ if ("Poids_total"%in%colnames(data)){
+ aat_bilanmigrationjournalier_bjo=cbind(
+ bilanMigration at dc@dc_selectionne,
+ bilanMigration at taxons@data$tax_code,
+ bilanMigration at stades@data$std_code,
+ annee, # une valeur
+ rep(jour_dans_lannee_non_nuls,ncol(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","Effectif_total.p","Effectif_total.e","poids_depuis_effectifs","Poids_total","taux_d_echappement","coe_valeur_coefficient")])),
+ utils::stack(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","Effectif_total.p","Effectif_total.e","poids_depuis_effectifs","Poids_total","taux_d_echappement","coe_valeur_coefficient")]),
+ Sys.time(),
+ substr(toupper(get("sch",envir=envir_stacomi)),1,nchar(toupper(get("sch",envir=envir_stacomi)))-1)
+ )
+ } else{
+ aat_bilanmigrationjournalier_bjo=cbind(
+ bilanMigration at dc@dc_selectionne,
+ bilanMigration at taxons@data$tax_code,
+ bilanMigration at stades@data$std_code,
+ annee, # une valeur
+ rep(jour_dans_lannee_non_nuls,ncol(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","taux_d_echappement","coe_valeur_coefficient")])),
+ utils::stack(data[,c("MESURE","CALCULE","EXPERT","PONCTUEL","Effectif_total","taux_d_echappement","coe_valeur_coefficient")]),
+ Sys.time(),
+ substr(toupper(get("sch",envir=envir_stacomi)),1,nchar(toupper(get("sch",envir=envir_stacomi)))-1)
+ )
+ }
aat_bilanmigrationjournalier_bjo= stacomirtools::killfactor(aat_bilanmigrationjournalier_bjo[!is.na(aat_bilanmigrationjournalier_bjo$values),])
colnames(aat_bilanmigrationjournalier_bjo)<-c("bjo_dis_identifiant","bjo_tax_code","bjo_std_code","bjo_annee","bjo_jour","bjo_valeur","bjo_labelquantite","bjo_horodateexport","bjo_org_code")
Modified: pkg/stacomir/R/Bilan_poids_moyen.r
===================================================================
--- pkg/stacomir/R/Bilan_poids_moyen.r 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/R/Bilan_poids_moyen.r 2017-04-01 12:56:34 UTC (rev 331)
@@ -171,7 +171,7 @@
bilPM<-charge(bilPM)
bilPM<-connect(bilPM)
bilPM<-calcule(bilPM)
-
+
}
@@ -270,44 +270,46 @@
if (!silent) funout(gettext("object p assigned to envir_stacomi",domain="R-stacomiR"))
}
})
-
-
+
+
#' Internal handler for reg, class \code{\link{Bilan_poids_moyen-class}}.
#' @param h handler
#' @param \dots additional arguments passed to the function
- hreg = function(h,...) {
- bilPM<-get("bilan_poids_moyen",envir=envir_stacomi)
- model(bilPM,model.type=h$action)
- }
-
+hreg = function(h,...) {
+ bilPM<-get("bilan_poids_moyen",envir=envir_stacomi)
+ model(bilPM,model.type=h$action)
+}
+
#' model method for Bilan_poids_moyen'
#' this method uses samples collected over the season to model the variation in weight of
#' glass eel or yellow eels.
#' @param object An object of class \link{Bilan_pois_moyen-class}
#' @param model.type default "seasonal", "seasonal1","seasonal2","manual".
+#' @usage model(object,model.type=c("seasonal","seasonal1","seasonal2","manual"),silent=FALSE)
+#' @details
+#' Depending on model.type several models are produced
#' \itemize{
-#' \item{model.type="seasonal". The simplest model uses a seasonal variation, it is
+#'\item{model.type="seasonal".}{ The simplest model uses a seasonal variation, it is
#' fitted with a sine wave curve allowing a cyclic variation
#' w ~ a*cos(2*pi*(doy-T)/365)+b with a period T. The julian time d0 used is this model is set
#' at zero 1st of November d = d + d0; d0 = 305.}
-#' \item{model.type="seasonal1". A time component is introduced in the model, which allows
+#'\item{model.type="seasonal1".}{ A time component is introduced in the model, which allows
#' for a long term variation along with the seasonal variation. This long term variation is
#' is fitted with a gam, the time variable is set at zero at the beginning of the first day of observed values.
#' The seasonal variation is modeled on the same modified julian time as model.type="seasonal"
#' but here we use a cyclic cubic spline cc, which allows to return at the value of d0=0 at d=365.
#' This model was considered as the best to model size variations by Diaz & Briand in prep. but using a large set of values
#' over years.}
-#' \item{model.type="seasonal2". The seasonal trend in the previous model is now modelled with a sine
-#' curve similar to the sine curve used in seasonal. The formula for this is \eqn{sin(\omega vt) + cos(\omega vt)}{{sin(omega vt) + cos(omega vt)},
+#'\item{model.type="seasonal2".}{The seasonal trend in the previous model is now modelled with a sine
+#' curve similar to the sine curve used in seasonal. The formula for this is \eqn{sin(\omega vt) + cos(\omega vt)}{sin(omega vt) + cos(omega vt)},
#' where vt is the time index variable \eqn{\omega}{omega} is a constant that describes how the index variable relates to the full period
-#' (here, \eqn{2\pi/365=0.0172}{2pi/365=0.0172}). The model is written as following w~cos(0.0172*doy)+sin(0.0172*doy)+s(time).}
-#' \item{model.type="manual", The dataset don (the raw data), coe (the coefficients already present in the
+#' (here, \eqn{2\pi/365=0.0172}{2pi/365=0.0172}). The model is written as following \eqn{w~cos(0.0172*doy)+sin(0.0172*doy)+s(time).}}
+#'\item{model.type="manual".}{ The dataset don (the raw data), coe (the coefficients already present in the
#' database, and newcoe the dataset to make the predictions from, are written to the environment envir_stacomi.
#' please see example for further description on how to fit your own model, build the table of coefficients,
-#' and write it to the database.}
+#' and write it to the database.}
#' }
-#' @usage model(object,model.type=c("seasonal","seasonal1","seasonal2","manual"),silent=FALSE)
#' @author Cedric Briand \email{cedric.briand"at"eptb-vilaine.fr}
#' @aliases model.Bilan_poids_moyen model.bilPM
#' @export
@@ -325,8 +327,9 @@
if (!"date"%in%colnames(data)) stop ("date should be in colnames(data)")
if (!class(data$date)[1]=="POSIXct") stop("date should be POSIXct")
data$year<-lubridate::year(data$date)
+ # lubridate::yday(lubridate::dmy(01082008))
data$yday=lubridate::yday(data$date)
- data$doy=data$yday-305 # year begins in november
+ data$doy=data$yday-214 # year begins in august to be consistent with the class
data$season<-stringr::str_c(lubridate::year(data$date)-1,"-",lubridate::year(data$date)) # year-1-year
data$season[data$doy>0]<-stringr::str_c(lubridate::year(data$date),"-",lubridate::year(data$date)+1)[data$doy>0] # for november and december it's year - year+1
data$yearbis<-data$year # same as season but with a numeric
@@ -363,13 +366,16 @@
} else predata<-rbind(predata,predatay)
}
print(result)
+ assign("result",result,envir_stacomi)
+ if (!silent) funout(gettext("Model equations assigned to envir_stacomi (result)",domain="R-stacomiR"))
+
p<-ggplot(don)+ geom_jitter(aes(x=doy,y=w),col="aquamarine4")+facet_wrap(~season )+
geom_line(aes(x=doy,y=pred_weight),data=predata)+
#geom_line(aes(x=doy,y=pred_weight),color="green",size=1,data=predatafull[predatafull$doy==50,])+
theme_minimal()+
theme(panel.border = element_blank(),
axis.line = element_line())+
- xlab("Jour dans la saison, debut au 1er novembre")#,
+ xlab("Jour dans la saison, debut au 1er août")#,
#plot.background=element_rect(fill="darkseagreen"))#,
#panel.background = element_rect(fill = "grey90", colour = NA))
@@ -385,14 +391,14 @@
#points(as.POSIXct(newcoe$date),pred, col="magenta")
#legend("topright",c("Obs.", "Coeff base","Mod"), col=c("black","cyan","magenta"),pch="o",cex = 0.8)
#mtext(com,side=3,line=0.5)
- result
- result_to_text<-stringr::str_c(sapply(t(result[,c(1,3,4,5)]),as.character),collapse=" ")
-
+
+ result_to_text<-stringr::str_c(sapply(t(result[,c(1,3,4,5)]),as.character),collapse=" ")
+
# setting text for comment (lines inserted into the database)
com=stringr::str_c("w ~ a*cos(2*pi*(doy-T)/365)+b with a period T.",
" The julian time d0 used is this model is set at zero 1st of November doy = d + d0; d0 = 305.",
" Coefficients for the model (one line per season): season, a, T, b =",
- result_to_text)
+ result_to_text)
} else if (model.type=="seasonal1"){
g1 = mgcv::gam(w~s(yday,bs="cc")+s(time),data=don, knots = list(yday = c(1, 365)))
# the knots=list(yday=c(1,365) is necessary for a smooth construction of the model
@@ -423,7 +429,7 @@
# omega is a constant that describes how the index variable relates to the full period (here, 2pi/365=0.0172).
############################################################
g2 = mgcv::gam(w~cos(0.0172*doy)+sin(0.0172*doy)+s(time),data=don)
- print(gettext("One model per year, doy starts in november",domain="R-stacomiR"))
+ print(gettext("One model per year, doy starts in august",domain="R-stacomiR"))
summary(g2)
plot(g2,pages=1)
predata<-newcoe
@@ -444,7 +450,7 @@
assign("g2",g2,envir=envir_stacomi)
if (!silent) funout(gettext("ggplot object p assigned to envir_stacomi",domain="R-stacomiR"))
if (!silent) funout(gettext("gam model g2 assigned to envir_stacomi",domain="R-stacomiR"))
-
+
###################################################################
# comparison with Guerault and Desaunay (summary table in latex)
######################################################################
@@ -458,7 +464,7 @@
colnames(summary_harmonic)=c("source","$\\gamma$","$s_0(cm)$","$\\phi$")
xt_summary_harmonic<-xtable( summary_harmonic,
caption=gettext("Comparison of the coefficients obtained by \\citet{desaunay_seasonal_1997} and in the present modelling
- of estuarine samples.",domain="R-stacomiR"),
+ of estuarine samples.",domain="R-stacomiR"),
label=gettext("summary_harmonic",domain="R-stacomiR"),
digits=c(0,0,3,3,0))
tabname<-stringr::str_c(get("datawd",envir=envir_stacomi),"/summary_harmonic.tex")
@@ -485,24 +491,26 @@
assign("coe",coe,envir=envir_stacomi)
}
-
- import_coe=data.frame(
- "coe_tax_code"='2038',
- "coe_std_code"='CIV',
- "coe_qte_code"=1,
- "coe_date_debut"=Hmisc::round.POSIXt(predata$date,digits="days"),
- "coe_date_fin"=Hmisc::round.POSIXt(predata$date,digits="days")+as.difftime(1,units="days"),
- "coe_valeur_coefficient"=1/predata$pred_weight,
- "coe_commentaires"=com)
- # will write only if the database is present
- if (get("database_expected",envir_stacomi)){
- fileout= paste(get("datawd",envir=envir_stacomi),"import_coe",bilPM at anneedebut@annee_selectionnee,bilPM at anneefin@annee_selectionnee,".csv",sep="")
- utils::write.table(import_coe,file=fileout, row.names = FALSE,sep=";")
- funout(paste(gettextf("data directory :%s",fileout,domain="R-stacomiR")))
+ if (model.type!="manual"){
+ import_coe=data.frame(
+ "coe_tax_code"='2038',
+ "coe_std_code"='CIV',
+ "coe_qte_code"=1,
+ "coe_date_debut"=Hmisc::round.POSIXt(predata$date,digits="days"),
+ "coe_date_fin"=Hmisc::round.POSIXt(predata$date,digits="days")+as.difftime(1,units="days"),
+ "coe_valeur_coefficient"=1/predata$pred_weight,
+ "coe_commentaires"=com)
+ # will write only if the database is present
+ if (get("database_expected",envir_stacomi)){
+ fileout= paste(get("datawd",envir=envir_stacomi),"import_coe",bilPM at anneedebut@annee_selectionnee,bilPM at anneefin@annee_selectionnee,".csv",sep="")
+ utils::write.table(import_coe,file=fileout, row.names = FALSE,sep=";")
+ funout(paste(gettextf("data directory :%s",fileout,domain="R-stacomiR")))
+ }
+ assign("import_coe",import_coe,envir=envir_stacomi)
+ funout(gettext("To obtain the table, type : import_coe=get(import_coe\",envir_stacomi",domain="R-stacomiR"))
+ bilPM at calcdata[["import_coe"]]<-import_coe
}
- assign("import_coe",import_coe,envir=envir_stacomi)
- funout(gettext("To obtain the table, type : import_coe=get(import_coe\",envir_stacomi",domain="R-stacomiR"))
- bilPM at calcdata[["import_coe"]]<-import_coe
+ return(bilPM)
})
@@ -547,11 +555,13 @@
# first delete existing data from the database
supprime(bilPM at coe,tax=2038,std="CIV")
import_coe<-bilPM at calcdata$import_coe
+ import_coe$coe_org_code<-toupper(gsub("\\.","",get("sch",envir_stacomi)))
baseODBC<-get("baseODBC",envir=envir_stacomi)
sql<-stringr::str_c("INSERT INTO ",get("sch",envir=envir_stacomi),"tj_coefficientconversion_coe (",
"coe_tax_code,coe_std_code,coe_qte_code,coe_date_debut,coe_date_fin,coe_valeur_coefficient,
- coe_commentaires)",
- " SELECT * FROM import_coe;")
+ coe_commentaires,coe_org_code)",
+ " SELECT coe_tax_code,coe_std_code,coe_qte_code,coe_date_debut,coe_date_fin,coe_valeur_coefficient::real,
+ coe_commentaires,coe_org_code FROM import_coe;")
invisible(utils::capture.output(
sqldf::sqldf(x=sql,
drv="PostgreSQL",
Modified: pkg/stacomir/R/RefCoe.r
===================================================================
--- pkg/stacomir/R/RefCoe.r 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/R/RefCoe.r 2017-04-01 12:56:34 UTC (rev 331)
@@ -44,7 +44,7 @@
requete at colonnefin="coe_date_fin"
# the coefficients are only loaded for bilanMigration
# to be consistent with current programming, we need to add it as a timestamp
- requete at datefin=as.POSIXlt(object at datefin)+as.difftime("23:59:59")
+ requete at datefin=as.POSIXlt(object at datefin+as.difftime("23:59:59"))
requete at select=stringr::str_c("select * from ",
get("sch",envir=envir_stacomi),
"tj_coefficientconversion_coe")
Modified: pkg/stacomir/inst/examples/bilanAnnuels_example.R
===================================================================
--- pkg/stacomir/inst/examples/bilanAnnuels_example.R 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/inst/examples/bilanAnnuels_example.R 2017-04-01 12:56:34 UTC (rev 331)
@@ -5,7 +5,6 @@
database_expected=FALSE)
# the following script will load the Arzal dataset if connected to iav schema
\dontrun{
- #create an instance of the class
baseODBC<-get("baseODBC",envir=envir_stacomi)
baseODBC[c(2,3)]<-rep("iav",2)
assign("baseODBC",baseODBC,envir_stacomi)
@@ -23,6 +22,7 @@
}
# the following dataset has been generated by the previous code
data(bilA)
+(bilA)
xtbilA<-xtable(bilA,
dc_name=c("Passe bassins","Piege anguille RG","Piege anguille RD"),
tax_name="Anguille",
Modified: pkg/stacomir/inst/examples/bilan_poids_moyen_example.R
===================================================================
--- pkg/stacomir/inst/examples/bilan_poids_moyen_example.R 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/inst/examples/bilan_poids_moyen_example.R 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,8 +3,6 @@
stacomi(gr_interface=FALSE,
login_window=FALSE,
database_expected=FALSE)
-# the following script will load data from the two Anguillere monitored in the Somme
-
\dontrun{
#create an instance of the class
bilPM<-new("Bilan_poids_moyen")
Modified: pkg/stacomir/man/BilanAnnuels-class.Rd
===================================================================
--- pkg/stacomir/man/BilanAnnuels-class.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/BilanAnnuels-class.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -31,7 +31,6 @@
database_expected=FALSE)
# the following script will load the Arzal dataset if connected to iav schema
\dontrun{
- #create an instance of the class
baseODBC<-get("baseODBC",envir=envir_stacomi)
baseODBC[c(2,3)]<-rep("iav",2)
assign("baseODBC",baseODBC,envir_stacomi)
@@ -49,6 +48,7 @@
}
# the following dataset has been generated by the previous code
data(bilA)
+(bilA)
xtbilA<-xtable(bilA,
dc_name=c("Passe bassins","Piege anguille RG","Piege anguille RD"),
tax_name="Anguille",
Modified: pkg/stacomir/man/Bilan_poids_moyen-class.Rd
===================================================================
--- pkg/stacomir/man/Bilan_poids_moyen-class.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/Bilan_poids_moyen-class.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -42,8 +42,6 @@
stacomi(gr_interface=FALSE,
login_window=FALSE,
database_expected=FALSE)
-# the following script will load data from the two Anguillere monitored in the Somme
-
\dontrun{
#create an instance of the class
bilPM<-new("Bilan_poids_moyen")
Modified: pkg/stacomir/man/bMM_Arzal.Rd
===================================================================
--- pkg/stacomir/man/bMM_Arzal.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bMM_Arzal.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,7 +3,7 @@
\docType{data}
\name{bMM_Arzal}
\alias{bMM_Arzal}
-\title{An object of class bilanMigrationMult with data loaded}
+\title{Anguilla migration at the Arzal station (BilanMigrationMult-class)}
\format{An object of class bilanMigrationMult with slots:
\describe{
\item{dc}{the \code{RefDC} object filled with data}
Modified: pkg/stacomir/man/bM_Arzal.Rd
===================================================================
--- pkg/stacomir/man/bM_Arzal.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bM_Arzal.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,7 +3,7 @@
\docType{data}
\name{bM_Arzal}
\alias{bM_Arzal}
-\title{An object of class bilanMigration with data loaded}
+\title{Video counting of thin lipped mullet (Liza ramada) in 2015 on the Vilaine (France)}
\format{An object of class bilanMigration with 8 slots:
\describe{
\item{dc}{the \code{RefDC} object with 4 slots filled with data corresponding to the iav postgres schema}
Modified: pkg/stacomir/man/b_carlot.Rd
===================================================================
--- pkg/stacomir/man/b_carlot.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/b_carlot.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,8 +3,8 @@
\docType{data}
\name{b_carlot}
\alias{b_carlot}
-\title{An object of class \link{Bilan_carlot-class} with data loaded}
-\format{An object of class Bilan_carlot}
+\title{Size of yellow and glass eel at the Arzal dam (Vilaine, France) in the fishway and main eel trapping ladder.}
+\format{An object of class \link{Bilan_carlot-class}}
\usage{
b_carlot
}
Modified: pkg/stacomir/man/bfDC.Rd
===================================================================
--- pkg/stacomir/man/bfDC.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bfDC.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,7 +3,7 @@
\docType{data}
\name{bfDC}
\alias{bfDC}
-\title{An object of class \link{BilanFonctionnementDC-class} with data loaded}
+\title{Counting Device (DC) operation from 2000 to 2015 at the Arzal dam (Vilaine, France)}
\format{An object of class BilanFonctionnementDC with 4 slots:
\describe{
#' \item{data}{ A dataframe with 544 obs. of 7 variables
@@ -32,7 +32,8 @@
}
\description{
This data corresponds to the data collected at the vertical slot fishway camera
-from 2000 to 2015.
+from 2000 to 2015. It represents an object of class \link{BilanFonctionnementDC-class}
+with data loaded
}
\keyword{data}
Modified: pkg/stacomir/man/bfDF.Rd
===================================================================
--- pkg/stacomir/man/bfDF.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bfDF.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,7 +3,7 @@
\docType{data}
\name{bfDF}
\alias{bfDF}
-\title{An object of class \link{BilanFonctionnementDF-class} with data loaded}
+\title{Overview of the fishway operation at Arzal in (Vilaine France).}
\format{An object of class BilanFonctionnementDF with 4 slots:
\describe{
#' \item{data}{ A dataframe with 4261 obs. of 7 variables
@@ -31,7 +31,8 @@
}
\description{
This data corresponds to the data collected at the vertical slot fishway
-in 2015, the fishway is working daily with a cycle depending on tide.
+in 2015, the fishway is working daily with a cycle depending on tide. This dataset
+is used to show an example of acdetailed output for an object of class \link{BilanFonctionnementDF-class} with data loaded
}
\keyword{data}
Modified: pkg/stacomir/man/bilA.Rd
===================================================================
--- pkg/stacomir/man/bilA.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bilA.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,7 +3,8 @@
\docType{data}
\name{bilA}
\alias{bilA}
-\title{An object of class \link{BilanAnnuels-class} with data loaded}
+\title{Annual migration of yellow and silver eel for three fishways / counting devices at the
+Arzal dam (data from 1995 to 2016)}
\format{An object of class \link{BilanAnnuels-class} with data slot loaded.}
\usage{
bilA
Modified: pkg/stacomir/man/bilanFonctionnementDC.Rd
===================================================================
--- pkg/stacomir/man/bilanFonctionnementDC.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bilanFonctionnementDC.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,13 +3,14 @@
\docType{data}
\name{bilanFonctionnementDC}
\alias{bilanFonctionnementDC}
-\title{An object of class \link{BilanFonctionnementDC-class} with data loaded}
+\title{Counting device operation for three different counting device in Arzal (Vilaine, France)}
\format{An object of class BilanFonctionnementDC}
\usage{
bilanFonctionnementDC
}
\description{
-This dataset corresponds to the data collected at three different control devices
+This dataset corresponds to the data collected at three different control devices.
+This object is of class \link{BilanFonctionnementDC-class} with data loaded
it is loaded along with \link{bMM_Arzal}
}
\keyword{data}
Modified: pkg/stacomir/man/bilanFonctionnementDF.Rd
===================================================================
--- pkg/stacomir/man/bilanFonctionnementDF.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bilanFonctionnementDF.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,8 +3,8 @@
\docType{data}
\name{bilanFonctionnementDF}
\alias{bilanFonctionnementDF}
-\title{An object of class \link{BilanFonctionnementDF-class} with data loaded}
-\format{An object of class BilanFonctionnementDF}
+\title{Fishway operation at the Arzal Dam (Vilaine France) (3 Fishways in 2011)}
+\format{An object of class BilanFonctionnementDF \link{BilanFonctionnementDF-class}}
\usage{
bilanFonctionnementDF
}
Modified: pkg/stacomir/man/bilanOperation.Rd
===================================================================
--- pkg/stacomir/man/bilanOperation.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bilanOperation.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,13 +3,14 @@
\docType{data}
\name{bilanOperation}
\alias{bilanOperation}
-\title{An object of class \link{BilanOperation-class} with data loaded}
+\title{Counting operations for three different counting device in Arzal (Vilaine, France)}
\format{An object of class BilanOperation}
\usage{
bilanOperation
}
\description{
This dataset corresponds to the data collected at three different control devices
+It is an object of class \link{BilanOperation-class} with data loaded.
it is loaded along with \link{bMM_Arzal}
}
\keyword{data}
Modified: pkg/stacomir/man/bmi.Rd
===================================================================
--- pkg/stacomir/man/bmi.Rd 2017-03-30 18:28:22 UTC (rev 330)
+++ pkg/stacomir/man/bmi.Rd 2017-04-01 12:56:34 UTC (rev 331)
@@ -3,8 +3,8 @@
\docType{data}
\name{bmi}
\alias{bmi}
-\title{An object of class \link{BilanMigrationInterAnnuelle-class} with data loaded}
-\format{An object of class BilanMigrationInterAnnuelle-class with data slot loaded.}
+\title{Daily glass eel and elver migration from 1984 to 2016 in the Sèvre Niortaise}
+\format{An object of class \ref{BilanMigrationInterAnnuelle-class} with data loaded.}
\usage{
bmi
}
Added: pkg/stacomir/man/model-Bilan_poids_moyen-method.Rd.tex
===================================================================
--- pkg/stacomir/man/model-Bilan_poids_moyen-method.Rd.tex (rev 0)
+++ pkg/stacomir/man/model-Bilan_poids_moyen-method.Rd.tex 2017-04-01 12:56:34 UTC (rev 331)
@@ -0,0 +1,51 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/Bilan_poids_moyen.r
+\docType{methods}
+\name{model,Bilan_poids_moyen-method}
+\alias{model,Bilan_poids_moyen-method}
+\alias{model.Bilan_poids_moyen}
+\alias{model.bilPM}
+\title{model method for Bilan_poids_moyen'
+this method uses samples collected over the season to model the variation in weight of
+glass eel or yellow eels.}
+\usage{
+model(object,model.type=c("seasonal","seasonal1","seasonal2","manual"),silent=FALSE)
+}
+\arguments{
+\item{object}{An object of class \link{Bilan_pois_moyen-class}}
+
+\item{model.type}{default "seasonal", "seasonal1","seasonal2","manual".}
+}
+\description{
+model method for Bilan_poids_moyen'
+this method uses samples collected over the season to model the variation in weight of
+glass eel or yellow eels.
+}
+\details{
+Depending on model.type several models are produced
+\itemize{
+ \item{model.type="seasonal".}{ The simplest model uses a seasonal variation, it is
+ fitted with a sine wave curve allowing a cyclic variation
+ w ~ a*cos(2*pi*(doy-T)/365)+b with a period T. The julian time d0 used is this model is set
+ at zero 1st of November d = d + d0; d0 = 305.}
+ \item{model.type="seasonal1".}{ A time component is introduced in the model, which allows
+ for a long term variation along with the seasonal variation. This long term variation is
+ is fitted with a gam, the time variable is set at zero at the beginning of the first day of observed values.
+ The seasonal variation is modeled on the same modified julian time as model.type="seasonal"
+ but here we use a cyclic cubic spline cc, which allows to return at the value of d0=0 at d=365.
+ This model was considered as the best to model size variations by Diaz & Briand in prep. but using a large set of values
+ over years.}
+\item{model.type="seasonal2"}{The seasonal trend in the previous model is now modelled with a sine
+ curve similar to the sine curve used in seasonal. The formula for this is \eqn{sin(\omega vt) + cos(\omega vt)}{sin(omega vt) + cos(omega vt)},
+ where vt is the time index variable \eqn{\omega}{omega} is a constant that describes how the index variable relates to the full period
+ (here, \eqn{2\pi/365=0.0172}{2pi/365=0.0172}. The model is written as following \eqn{w~cos(0.0172*doy)+sin(0.0172*doy)+s(time).}}
+ \item{model.type="manual"}{ The dataset don (the raw data), coe (the coefficients already present in the
+ database, and newcoe the dataset to make the predictions from, are written to the environment envir_stacomi.
+ please see example for further description on how to fit your own model, build the table of coefficients,
+ and write it to the database.}
+}
+}
+\author{
+Cedric Briand \email{cedric.briand"at"eptb-vilaine.fr}
+}
+
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