In ldbk/wksdecc: Fishframe to another format

knitr::opts_chunk$set(dev='png')
library(WKSDECC)
library(dplyr)
library(pander)

WKSDECC format

Some words and a figure.

Sole in the 27.4

Sole in the 27.4 area.

France

Sampling design

A description of the sampling design. Sampling at sea and on port.

Sampling at sea

At sea sampling from a vessel list, then the voyage of the vessel, part of the hauls are sampled.

• strata 1: quarter
• PSU : vessel x day

Sampling plan by quarter/area/metier. Vessels are selected according to the area/metier strata, then some fishing operation for a trip are sampled at sea if it matches the strata. For port sampling, the trip is sampled if it matches the area/metier strata conditions.

Sampling at port

Fishframe data

France data

• COSTcore package:

#read the sole 27.4 data for 2016
pathsol<-"/home/moi/ifremer/analyses_stock_2017/WGNSSK/sol.27.4/data/"
load(paste0(pathsol,"CSr2016.rdata"))
load(paste0(pathsol,"CLr2016.rdata"))
load(paste0(pathsol,"CEr2016.rdata"))
#read sampling plan
planobsmer<-read.csv2("/home/moi/ifremer/data/wao/plan_OBSMER_2016.csv")
planobsvente<-read.csv2("/home/moi/ifremer/data/wao/plan_OBSVENTE_2016.csv")
#remove COSTcore dependency : cost object to dataframe
cl<-CLr@cl
ce<-CEr@ce
tr<-CSr@tr
hh<-CSr@hh
sl<-CSr@sl
hl<-CSr@hl
ca<-CSr@ca

require(digest)
anonymize <- function(x, algo="crc32"){
    unq_hashes <- vapply(unique(x), function(object) digest(object,algo=algo),
                     FUN.VALUE="", USE.NAMES=TRUE)
    unname(unq_hashes[x])
}
CSr@tr$vslId<- anonymize(as.character(CSr@tr$vslId))

write.table(CLr@cl,file="cl.csv",sep=";",row.names=F,col.names=T)
write.table(CEr@ce,file="ce.csv",sep=";",row.names=F,col.names=T)
write.table(CSr@tr,file="tr.csv",sep=";",row.names=F,col.names=T)
write.table(CSr@hh,file="hh.csv",sep=";",row.names=F,col.names=T)
write.table(CSr@sl,file="sl.csv",sep=";",row.names=F,col.names=T)
write.table(CSr@hl,file="hl.csv",sep=";",row.names=F,col.names=T)
write.table(CSr@ca,file="ca.csv",sep=";",row.names=F,col.names=T)

Generic version: each table (cl, ce, tr, hh, sl, hl, ca) in a text file (; sep) with a header.

pathdatacsv<-"/home/moi/ifremer/WKSDECC/datacsv/"
cl<-read.table(paste0(pathdatacsv,"cl.csv"),sep=";",header=T)
ce<-read.table(paste0(pathdatacsv,"ce.csv"),sep=";",header=T)
tr<-read.table(paste0(pathdatacsv,"tr.csv"),sep=";",header=T)
hh<-read.table(paste0(pathdatacsv,"hh.csv"),sep=";",header=T)
sl<-read.table(paste0(pathdatacsv,"sl.csv"),sep=";",header=T)
hl<-read.table(paste0(pathdatacsv,"hl.csv"),sep=";",header=T)
ca<-read.table(paste0(pathdatacsv,"ca.csv"),sep=";",header=T)

This report uses the 7 tables from the fishframe format.

    pander(head(cl))

    pander(head(ce))

    pander(head(tr))

    pander(head(hh))

    pander(head(sl))

    pander(head(hl))

    pander(head(ca))

DEsign table

We call it DE. Two design: one for at sea sampling (OBSMER program), one for port sampling (OBSVENTE program). This table is not build using fishframe information.

    DE<-createdf("Design",nbrow=2)
    DE<-DE%>%mutate(designID=c(1,2),
          recType="DE",
          sampScheme=c("obsmer","obsvente"),
          sampStrata="",
          hierarchy=c("",
              ""))

    pander(DE)

Sampling Event table

We call it SE. The table use the information from the hh and tr table from fishframe sampling table (CS object), and from the population data related to effort (CE object). A sampling event is related to a trip for port sampling and for hauls for at sea sampling.

###########################################################
#tr and hh tables are merged
hh<-hh%>%mutate(trpCode=as.character(trpCode))
hhtr<-left_join(hh,tr)%>%
    mutate(month=as.numeric(substr(date,6,7)))

#build sampling event population data info using CE
nbtruc<-ce%>%group_by(harbour,month,foCatEu6)%>%summarise(nbtr=sum(trpNum),
                              nbfo=sum(foNum),
                              nbday=sum(daysAtSea))%>%ungroup()

hhtr<-left_join(hhtr,nbtruc)
#split by at sea vs port
hhsea<-hhtr%>%filter(sampType=="S")%>%mutate()
hhport<-hhtr%>%filter(sampType=="M")
SEatsea<-createdf("Sampling Event",nbrow=nrow(hhsea))
SEport<-createdf("Sampling Event",nbrow=nrow(hhport))
#at sea
SEatsea<-SEatsea%>%mutate(sampEventID=paste(hhsea$trpCode,hhsea$staNum),
              designID=1,
              recType="SE",
              seYear=substr(hhsea$date,1,4),
              sampDate=as.character(hhsea$date),
              sampTime=as.character(hhsea$time),
              sampCtry="FRA",
              sampUnit="quarter*area*port*metier*vessel",
              sampMeth="Observer",
              seUnitTotal=as.character(hhsea$nbtr),
              seUnitSampled="1",
              selectionMethod="adhoc"
              )
SEport<-SEport%>%mutate(sampEventID=paste(hhport$trpCode,hhport$staNum),
              designID=2,
              recType="SE",
              seYear=substr(hhport$date,1,4),
              sampDate=as.character(hhport$date),
              sampTime=as.character(hhport$time),
              sampCtry="FRA",
              sampUnit="quarter*area*port*metier*vessel",
              sampMeth="Observer",
              seUnitTotal=as.character(hhport$nbtr),
              seUnitSampled="1",
              selectionMethod="adhoc"
              )
SE<-rbind(SEatsea,SEport)%>%mutate(seSampProb=as.numeric(seUnitSampled)/as.numeric(seUnitTotal))

 pander(head(SE))

VEssel table

VE table. Hard to fill without external information : the number of vessels is not recorded in CE table.

########################################################
#Vessel table
vesseltab<-hhtr%>%select(vslId,trpCode,staNum,vslLen,vslPwr,vslSize)%>%
            distinct()%>%mutate(sampEventID=paste(trpCode,staNum))%>%
            select(-trpCode,-staNum)
VE<-createdf("Vessel",nbrow=nrow(vesseltab))
#pick value matching names of the vessel table
VE<-pickvalue(VE,vesseltab)

 pander(head(VE))

VOyage table

VO table. Some cosmetic information are not available in the CS and CE object (departure and arrival information mainly). It's a simple version of the tr table.

    VOinit<-hhtr%>%mutate(voyageID=trpCode,
              sampEventID=paste(trpCode,staNum),
              vslTblID=vslId,
              recType="VO",
              arvLoc=harbour,
              voyageTotal=nbtr,
              voyageSampled=1,
              voyageSampProb=voyageSampled/voyageTotal
            )
    VO<-createdf("Voyage",nbrow=nrow(VOinit))
    #pick value matching names of the sl table
    VO<-pickvalue(VO,VOinit)

 pander(head(VO))

Fishing Operation table

FO table. Very similar to the hh table.

    FOinit<-hhtr%>%mutate(foID=staNum,
                  voyageID=trpCode,
                  foDate=date,
                  foTime=time,
                  recType="FO",
                  subRect=NA,
                  aggLev=as.character(aggLev),
                  foTotal=nbfo,
                  foSampled=1,
                  foSampProb=foSampled/foTotal)
    FO<-createdf("Fishing Operation",nbrow=nrow(FOinit))
    #pick value matching names of the sl table
    FO<-pickvalue(FO,FOinit)

 pander(head(FO))

SAmple table

SA table. Very similar to the sl table.

    #tr and hh tables are merged
    sl<-sl%>%mutate(trpCode=as.character(trpCode))
    slhh<-left_join(sl,hh)

    SAinit<-slhh%>%mutate(sampID=paste(trpCode,staNum),
                  foID=staNum,
                  voyageID=trpCode,
                  recType="SA",
                  commSpp="SOL",
                  sppName=spp,
                  sampWt=subSampWt,
                  unitTotal=wt,
                  unitSampled=sampWt,
                  unitSampProb=unitSampled/unitTotal,
                  concurrent="yes")
    SA<-createdf("Sample",nbrow=nrow(SAinit))
    #pick value matching names of the sl table
    SA<-pickvalue(SA,SAinit)

 pander(head(SA))

Frequency Measure table

FM table: similar to the hl table.

    #tr and hh tables are merged
    hl<-hl%>%mutate(trpCode=as.character(trpCode))
    hlsl<-left_join(hl,sl)

    FMinit<-hlsl%>%mutate(freqMesID=paste(1:nrow(hlsl)),
                  sampID=paste(trpCode,staNum),
                  foID=staNum,
                  voyageID=trpCode,
                  recType="FM",
                  commSpp="SOL",
                  sppName=spp)

    FM<-createdf("Frequency Measure",nbrow=nrow(FMinit))
    #pick value matching names of the sl table
    FM<-pickvalue(FM,FMinit)
    #add info
    FM<-FM%>%group_by(sampID)%>%mutate(fishSampled=sum(lenNum))%>%ungroup()
    #number of fish total should be computed but later (multiple regression
    #using sampWt and number of fish)

 pander(data.frame(FM[1:5,]))

Biological Variable table

BV table: similar to the ca table.

    #tr and hh tables are merged
    hl<-hl%>%mutate(trpCode=as.character(trpCode))
    hlsl<-left_join(hl,sl)

    FMinit<-hlsl%>%mutate(freqMesID=paste(1:nrow(hlsl)),
                  sampID=paste(trpCode,staNum),
                  foID=staNum,
                  voyageID=trpCode,
                  recType="FM",
                  commSpp="SOL",
                  sppName=spp)

    FM<-createdf("Frequency Measure",nbrow=nrow(FMinit))
    #pick value matching names of the sl table
    FM<-pickvalue(FM,FMinit)
    #add info
    FM<-FM%>%group_by(sampID)%>%mutate(fishSampled=sum(lenNum))%>%ungroup()
    #number of fish total should be computed but later (multiple regression
    #using sampWt and number of fish)

XX table

XX table: similar to the hl table.

ldbk/wksdecc documentation built on May 5, 2019, 8:02 p.m.