#' Extract Length at Age data CFDBS
#'
#'Extract a list of length and ages for speices sampled in Commercial fisheries data.
#'This data is extracted from ADIOS (MV_CF_AGE)
#'
#' @param channel DBI Object. Inherited from \link[DBI]{DBIConnection-class}. This object is used to connect
#' to communicate with the database engine. (see \code{\link{connect_to_database}})
#' @param species A specific species code or set of codes. Either numeric or character vector. Defaults to "all" species.
#' Numeric codes are converted to VARCHAR2(3 BYTE) when creating the sql statement. Character codes are short character strings.
#' @param sex Character vector. Default = "all". options "M" (male), "F" (female), "U" (unsexed)
#' @param area Character or numeric vector. Statistical areas from which to pull ages. Default = "all"
#'
#' @return A list is returned:
#'
#' \item{data}{containing the result of the executed \code{$sql} statement}
#'
#' \item{sql}{containing the sql call}
#'
#' \item{colNames}{a vector of the table's column names}
#'
#'The default sql statement "\code{select * from stockeff.mv_cf_age}" is used
#'
#'@section Reference:
#'Use the data dictionary (\url{http://nova.nefsc.noaa.gov/datadict/}) for field name explanations.
#'Note: species codes (nespp3) are stored in the database as VARCHAR2(3 BYTE)
#'
#' @family get functions
#'
#' @seealso \code{\link{connect_to_database}}
#'
#' @examples
#' \dontrun{
#' # extracts all length and age data for all species defined as male or female (unsexed not included)
#' channel <- connect_to_database(server="name_of_server",uid="individuals_username")
#' get_length_age(channel,sex=c("M","F"))
#'
#' # extracts info for cod (081)
#' channel <- connect_to_database(server="name_of_server",uid="individuals_username")
#' get_length_age(channel,species=81)
#'
#' # extracts info for cod ("COD")
#' channel <- connect_to_database(server="name_of_server",uid="individuals_username")
#' get_length_age(channel,"cod") or
#' get_length_age(channel,"co") or
#' get_length_age(channel,"COD")
#'
#'}
#'
#' @export
get_age_length <- function(channel, year=1994, species="all", species_itis=FALSE, sex="all", area = "all"){
# create an SQL query to extract all relavent data from tables
# list of strings to build where clause in sql statement
whereVec <- list()
if (species_itis == FALSE) {
whereVec[[1]] <- dbutils::createString(itemName="nespp3",species,convertToCharacter=TRUE,numChars=3)
} else {
whereVec[[2]] <- dbutils::createString(itemName="species_itis",species,convertToCharacter=TRUE,numChars=6)
}
whereVec[[3]] <- dbutils::createString(itemName="year",year,convertToCharacter=TRUE,numChars=4)
# sex conversion
if (tolower(sex) == "all") {
sex <- c(0,1,2)
} else if (!is.numeric(sex)) {
sex <- gsub("M",1,sex)
sex <- gsub("F",2,sex)
sex <- as.numeric(gsub("U",0,sex))
}
whereVec[[4]] <- paste("sex in (",toString(sex),")")
# add area
whereVec[[5]] <- dbutils::createString(itemName="area",area,convertToCharacter=TRUE,numChars=3)
# build where clause of SQL statement based on input above
whereStr <- "where"
for (item in whereVec) {
if (is.null(item)) {next}
if (which(item == whereVec) == length(whereVec)) {
whereStr <- paste(whereStr,item)
next
}
whereStr <- paste(whereStr,item,"and")
}
# need to have length and numlen in ADIOS for comlens script to work
# eventually user will be able to pass these variables
sqlStatement <- "select year, AREA, QTR, NEGEAR, sex, age, length, numage
from stockeff.mv_cf_age"
sqlStatement <- paste(sqlStatement,whereStr)
# call database
query <- DBI::dbGetQuery(channel,sqlStatement)
# column names
sqlcolName <- "select COLUMN_NAME from ALL_TAB_COLUMNS where TABLE_NAME = 'MV_CF_AGE' and owner='STOCKEFF';"
colNames <- DBI::dbGetQuery(channel,sqlcolName)
query$YEAR <- as.integer(query$YEAR)
query$SEX <- as.integer(query$SEX)
query$QTR <- as.numeric(query$QTR)
return (list(data=dplyr::as_tibble(query),sql=sqlStatement, colNames=colNames))
}
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