R/imarpeSurvey.output-class.R

In imarpe/path: Pelagic Assessment Tools for Hydroacoustics

# print method
print.imarpeSurvey.output <- function(object, ...){
  
  sp  = object$info$sp
  var = "biomass" 
  units = list(abundance="1e6 individuals", biomass="tonnes",
               distance="nm", latitude="ºS", longitude="ºW", 
               length=getSpeciesInfo(sp)$unit)
  
  x = path:::.getOutput(object, stock="nc", var=var)
  
  mes = sprintf("Results for %s (%s) hydroacoustic assessment",
                getSpeciesInfo(sp)$display.name,
                getSpeciesInfo(sp)$sci.name)
  mes2 = sprintf("Survey: Cr-%s", object$info$surveyName)
  mes3 = sprintf("Total %s: %f %s\n", var, floor(x$total), units[[var]])
  cat2(c(mes, mes2, mes3), append=FALSE)
  
  return(invisible())
}

# summary method
summary.imarpeSurvey.output = function(object, what = "grouped",...){
  
  if(what == "grouped"){
    out <- object$results$info
  }else{
    out <- object$data[[1]]
  }
  
  return(out)
}

# print.summary method
print.summary.imarpeSurvey.output <- function(object, what = "grouped", ...){
  if(what == "grouped"){
    out <- sapply(object$out, summary)[c(1, 4, 6),]
  }else{
    out <- summary(object$out)
  }
  
  return(invisible())
}


plot.imarpeSurvey.output = function(object, sp = "anchoveta", ...) {
  
  specie = getSpeciesInfo(sp, data=NULL) # get species info
  
  old.par = par(no.readonly = TRUE)
  on.exit(par(old.par))
  
  par(mfrow=c(2,1), mar=c(0,0,0,0), oma=3*c(1.5,1.5,1,1.5))
  
  x = object$results$nc$biomass$length # filter data
  
  if(sum(x, na.rm = TRUE) > 0)
    .plotFreqsBase(x, specie, xaxis=FALSE, ...)
  
  
  x = object$results$nc$abundance$length # filter data
  
  if(sum(x, na.rm = TRUE) > 0)
    .plotFreqsBase(x, specie, yside=4, speciesInfo=FALSE, ...)
  
  
  par(mfrow=c(1,1))
  
  x_temp = object$results$total$abundance$lat_L # filter data
  temp = rownames(x_temp)
  temp = as.numeric(temp)
  x = cbind(temp, x_temp)
  x = as.data.frame(x)
  
  if(sum(x, na.rm = TRUE) > 0)
    .crea.fig.tallas(data = x, typedata = "lat", ...)
  
  
  par(mfrow=c(1,1))
  
  x_temp = object$results$total$abundance$dc_L # filter data
  temp = rownames(x_temp)
  temp = as.numeric(temp)
  x = cbind(temp, x_temp)
  x = as.data.frame(x)
  
  if(sum(x, na.rm = TRUE) > 0)
    .crea.fig.tallas(data = x, typedata = "dc", ...)
  
  return(invisible())
  
}