R/plot_market_code_by_time.R

In NOAA-EDAB/neusCatch: Multispecies length expansion of commercial catch

#' plots Number of length samples
#'
#'A facet grid for each gear type by market code and quarter year
#'Eventually generalize to semester or annually
#'
#'@param data List. landings and length data aggregated to some level
#'@param plotID numeric scalar. number ID of plot
#'@param outputDir Character string. Path to output directory (png files saved here)
#'@param outputPlots Boolean. Should plots be created. T or F
#'
#'@return Nothing
#'
#'@noRd

plot_market_code_by_time <- function(data,plotID,outputDir,outputPlots=T,aggregate_to = "QTR") {

  if (outputPlots == F) return()

  # aggregate data to plot
  if (aggregate_to == "YEAR") {
    # join landings and lengths to plot length distribution over time
    #aggegate over QTRs
    dataAgg <- output_data(data,aggregate_to)

    ddjoin <- dataAgg$landings %>%
      dplyr::left_join(.,dataAgg$lengthData,by = c("YEAR","NEGEAR","MARKET_CODE"))

    # for each geartype
    for (gearType in unique(dataAgg$landings$NEGEAR)) {

      png(paste0(outputDir,"/",plotID+2,"_market_category_",aggregate_to,"_lengths_",as.character(gearType),".png"))

      dd <- ddjoin %>% dplyr::filter(NEGEAR == gearType) %>% dplyr::filter(len_numLengthSamples != 0)

      p <- ggplot2::ggplot(data = dd) +
        ggplot2::geom_boxplot(mapping = ggplot2::aes(x=YEAR, y=LENGTH, group=YEAR)) +
        ggplot2::facet_grid(rows=ggplot2::vars(MARKET_CODE))+
        ggplot2::ggtitle(paste0("Length distributions by Market Code and ",aggregate_to," (gear type = ",as.character(gearType),")")) +
        ggplot2::ylab("Length (cm)")
      print(p)
      dev.off()

      # Take a look at length distribution by QTR and MARKET CODE
      d <- dataAgg$lengthData %>% dplyr::filter(NEGEAR == gearType) %>%
        dplyr::group_by(MARKET_CODE,.data[[aggregate_to]],LENGTH) %>%
        dplyr::summarise(numlens=sum(as.numeric(NUMLEN)),.groups = "drop")

      # check to see if any lengths
      if(nrow(d) > 0) {
        png(paste0(outputDir,"/",plotID+3,"_market_category_",aggregate_to,"_length_distribution_",as.character(gearType),".png"))

        p <-   ggplot2::ggplot(data = d) +
          ggplot2::geom_bar(stat="identity",mapping= ggplot2::aes(x=LENGTH,y=numlens),na.rm=T) +
          ggplot2::facet_grid(cols=ggplot2::vars(MARKET_CODE)) +
          ggplot2::ggtitle(paste0("By ",aggregate_to," and MARKET_CODE  (gear type = ",as.character(gearType),")")) +
          ggplot2::ylab("Number at length")
        print(p)

        dev.off()
      }
    }
  }


  if (aggregate_to == "YEAR") {
    aggregate_to <- "QTR"
  }

  # join landings and lengths to plot length distribution over time
  ddjoin <- data$landings %>%
    dplyr::left_join(.,data$lengthData,by = c("YEAR",aggregate_to,"NEGEAR","MARKET_CODE"))

  # for each geartype
  for (gearType in unique(data$landings$NEGEAR)) {

    png(paste0(outputDir,"/",plotID,"_market_category_",aggregate_to,"_lengths_",as.character(gearType),".png"))

    dd <- ddjoin %>% dplyr::filter(NEGEAR == gearType) %>% dplyr::filter(len_numLengthSamples != 0)

    p <- ggplot2::ggplot(data = dd) +
      ggplot2::geom_boxplot(mapping = ggplot2::aes(x=YEAR, y=LENGTH, group=YEAR)) +
      ggplot2::facet_grid(rows=ggplot2::vars(MARKET_CODE),cols=ggplot2::vars(.data[[aggregate_to]]))+
      ggplot2::ggtitle(paste0("Length distributions by Market Code and ",aggregate_to," (gear type = ",as.character(gearType),")")) +
      ggplot2::ylab("Length (cm)")
    print(p)
    dev.off()

    # Take a look at length distribution by QTR and MARKET CODE
    d <- data$lengthData %>% dplyr::filter(NEGEAR == gearType) %>%
      dplyr::group_by(MARKET_CODE,.data[[aggregate_to]],LENGTH) %>%
      dplyr::summarise(numlens=sum(as.numeric(NUMLEN)),.groups = "drop")

    # check to see if any lengths
    if(nrow(d) > 0) {
      png(paste0(outputDir,"/",plotID+1,"_market_category_",aggregate_to,"_length_distribution_",as.character(gearType),".png"))

      p <-   ggplot2::ggplot(data = d) +
        ggplot2::geom_bar(stat="identity",mapping= ggplot2::aes(x=LENGTH,y=numlens),na.rm=T) +
        ggplot2::facet_grid(rows=ggplot2::vars(.data[[aggregate_to]]),cols=ggplot2::vars(MARKET_CODE)) +
        ggplot2::ggtitle(paste0("By ",aggregate_to," and MARKET_CODE  (gear type = ",as.character(gearType),")")) +
        ggplot2::ylab("Number at length")
      print(p)

      dev.off()
    }


  }
}