R/Bens_plot_pop_spatiotemp.R

In Blevy2/READ-PDB-blevy2-MFS2: Mixed Fishery fleet dynamics simulation tool

#' @title Plot population summary

#' @description \code{plot_pop_summary} plots the four population dynamic
#' metrics: catches, biomass, fishing mortality and recruitment.

#' It can either operate at a daily timestep or an annual timestep

#' @param results is an output from the function \link{run_sim}.
#' @param timestep is a character string determining whether the plot is
#' 'daily' or 'annual'
#' @param save is a logical whether to save the plot
#' @param save.location is a location (defaults to current directory)

#' @return is a ggplot of all the species and metrics as a faceted plot

#' examples
#' plot_pop_summary(results = res, timestep = 'daily', save = TRUE, location = '.') 
#' ## Not run

#' @export

Bens_plot_pop_spatiotemp <- function(results = res, timestep = 'daily', save = FALSE , plot_monthly = FALSE, save.location = NULL, plot_weekly = FALSE, ColBreaks = NULL) {
  
  
  
  
  
  #creating a plot similar to plot_spatiotemp_hab
  
  nrows <- nrow(res$pop_bios[[1]]$spp1) 
  ncols <- ncol(res$pop_bios[[1]]$spp1)
  
  
  if(plot_weekly == TRUE){
    
    for(s in seq_len(length(sim$idx[["n.spp"]]))) {  #number of species
      
      nt <- length(results[["pop_bios"]])  #number of weeks to plot
      if(!is.null(save.location)) {
        png(filename = paste0(save.location,'/','Population_spatiotemp_spp_',s,'.png'), width = 800, height = 800)
      }
      par(mfrow = c(ceiling(sqrt(nt)), ceiling(nt/ceiling(sqrt(nt)))), mar = c(1, 1, 1, 1))
      
      for(i in seq_len(nt-1)) {   #PLOTTED 1 LESS THAN END BECAUSE COMING UP NULL
        
        pop_wk <- results[["pop_bios"]][[i]][s]   
        
        
        
        image(results[["pop_bios"]][[i]][[paste0('spp',s)]], cex.axis = 1.5, cex.main = 2, col = grey(seq(1,0,l = 51)), axes = F)
        
        
        
        axis(1, at = seq(0, 1, by = 0.2), labels = seq(0, nrows, by = nrows/5))
        axis(2, at = seq(0, 1, by = 0.2), labels = seq(0, ncols, by = ncols/5))
        text(0.5, 0.98, labels = paste('week', i), cex = 1)
        
      }
      dev.off()
    }
    
  }
  
  
  
  
  
  
  
  if(plot_monthly == TRUE){
    
    #PART 1: If I have NOT created colbreaks, DONT use them
    if(is.null(ColBreaks)){
      if(!is.null(save.location)) {
        
        pdf(file=paste0(save.location,'/Monthly_pop_plots','.pdf'))
        #png(filename = paste0(plot.file,'/Monthly_covariate_plots/','monthly_habitat_spatiotemp_spp_',s,'month_',k,'.png'), width = 800, height = 800)
      }
      
      
      #relist so all pop values are in a sublist rather than 
      new_pop_bios <- list(list(),list())
      
      # new_pop_bios_singleList <- list(matrix(nc=100),matrix(nc=100))
      
      for(s in seq(length(hab[["hab"]]))){
        
        for(i in seq(length(res[["pop_bios"]]))){
          #print(s)
          #print(i)
          new_pop_bios[[s]][[i]] <- res$pop_bios[[i]][[s]]
          
          #   new_pop_bios_singleList[[s]] <- rbind(as.matrix(new_pop_bios_singleList[[s]]),as.matrix(res$pop_bios[[i]][[s]]))
          
        }
      }
      
      
      
      
      
      
      for(s in seq_len(length(hab[["hab"]]))) {
        

        
        for(k in seq(12)){
          
          nt <- length(res[["pop_bios"]])
          
          par(mfrow = c(5,4),mar = c(1, 1, 1, 1))
          
          
          for(i in seq(1,nt,52)){
            
            month_shift <- 4*(k-1)
            
            pop_wk <- new_pop_bios[[s]][[i+month_shift]]
            
            
            # fields::image.plot(pop_wk,  zlim = colrange )
            fields::image.plot(pop_wk )
            
            #	  axis(1, at = seq(0, 1, by = 0.2), labels = seq(0, nrows, by = nrows/5))
            #	  axis(2, at = seq(0, 1, by = 0.2), labels = seq(0, ncols, by = ncols/5))
            text(0.5, 0.98, labels = paste('week', i+month_shift), cex = 1)
            
            
          }
          
          
        }
      }
      
      dev.off()
      
      
      if(!is.null(res[["pop_bios_sd"]])){
        
        if(!is.null(save.location)) {
          
          pdf(file=paste0(save.location,'/Monthly_sd_plots','.pdf'))
          #png(filename = paste0(plot.file,'/Monthly_covariate_plots/','monthly_habitat_spatiotemp_spp_',s,'month_',k,'.png'), width = 800, height = 800)
        }
        
        
        
        for(s in seq_len(length(hab[["hab"]]))) {
          
          #set color range for spatial plots
          #colrange <- range(res[["pop_bios_sd"]][[s]],na.rm=TRUE)  #old method. now using own breaks
          
          Breaks = ColBreaks[[s+2]] #last two in list are for SD
          
          
          for(k in seq(12)){
            
            nt <- length(res[["pop_bios"]])
            
            par(mfrow = c(5,4),mar = c(1, 1, 1, 1))
            
            
            for(i in seq(1,nt,52)){
              
              month_shift <- 4*(k-1)
              
              pop_sd_wk <- res[["pop_bios_sd"]][[s]][[i+month_shift]]
              
              #fields::image.plot(pop_wk,  zlim = colrange )
              fields::image.plot(pop_sd_wk)
              
              #	  axis(1, at = seq(0, 1, by = 0.2), labels = seq(0, nrows, by = nrows/5))
              #	  axis(2, at = seq(0, 1, by = 0.2), labels = seq(0, ncols, by = ncols/5))
              text(0.5, 0.98, labels = paste('week', i+month_shift), cex = 1)
              
              
            }
            
            
          }
        }
        
        dev.off()
        
      }
      
      
      }
    
    

    
    
    
    #PART 2: If I have created colbreaks, use them
    if(!is.null(ColBreaks)){
    
    if(!is.null(save.location)) {
      
      pdf(file=paste0(save.location,'/Monthly_pop_plots','.pdf'))
      #png(filename = paste0(plot.file,'/Monthly_covariate_plots/','monthly_habitat_spatiotemp_spp_',s,'month_',k,'.png'), width = 800, height = 800)
    }
    
    
    #relist so all pop values are in a sublist rather than 
    new_pop_bios <- list(list(),list())
    
   # new_pop_bios_singleList <- list(matrix(nc=100),matrix(nc=100))
    
    for(s in seq(length(hab[["hab"]]))){
      
      for(i in seq(length(res[["pop_bios"]]))){
        #print(s)
        #print(i)
        new_pop_bios[[s]][[i]] <- res$pop_bios[[i]][[s]]
        
     #   new_pop_bios_singleList[[s]] <- rbind(as.matrix(new_pop_bios_singleList[[s]]),as.matrix(res$pop_bios[[i]][[s]]))
        
      }
    }
    
    
    
    
    
    
    for(s in seq_len(length(hab[["hab"]]))) {
      
      #set color range for spatial plots
     # colrange <- range(new_pop_bios[[s]],na.rm=TRUE) #old method. now using breaks
      
      Breaks = ColBreaks[[s]]   #1st two in list are for population values
      
      
      for(k in seq(12)){
        
        nt <- length(res[["pop_bios"]])
        
        par(mfrow = c(5,4),mar = c(1, 1, 1, 1))
        
        
        for(i in seq(1,nt,52)){
          
          month_shift <- 4*(k-1)
          
          pop_wk <- new_pop_bios[[s]][[i+month_shift]]
          
          
         # fields::image.plot(pop_wk,  zlim = colrange )
          fields::image.plot(pop_wk, breaks = Breaks, nlevel = length(Breaks)-1 )
          
          #	  axis(1, at = seq(0, 1, by = 0.2), labels = seq(0, nrows, by = nrows/5))
          #	  axis(2, at = seq(0, 1, by = 0.2), labels = seq(0, ncols, by = ncols/5))
          text(0.5, 0.98, labels = paste('week', i+month_shift), cex = 1)
          
          
        }
        
        
      }
    }
    
    dev.off()
    
    
    if(!is.null(res[["pop_bios_sd"]])){
      
      if(!is.null(save.location)) {
        
        pdf(file=paste0(save.location,'/Monthly_sd_plots','.pdf'))
        #png(filename = paste0(plot.file,'/Monthly_covariate_plots/','monthly_habitat_spatiotemp_spp_',s,'month_',k,'.png'), width = 800, height = 800)
      }
      
      
      
      for(s in seq_len(length(hab[["hab"]]))) {
        
        #set color range for spatial plots
        #colrange <- range(res[["pop_bios_sd"]][[s]],na.rm=TRUE)  #old method. now using own breaks
        
        Breaks = ColBreaks[[s+2]] #last two in list are for SD
        
        
        for(k in seq(12)){
          
          nt <- length(res[["pop_bios"]])
          
          par(mfrow = c(5,4),mar = c(1, 1, 1, 1))
          
          
          for(i in seq(1,nt,52)){
            
            month_shift <- 4*(k-1)
            
            pop_sd_wk <- res[["pop_bios_sd"]][[s]][[i+month_shift]]
            
            #fields::image.plot(pop_wk,  zlim = colrange )
            fields::image.plot(pop_sd_wk,  breaks = Breaks ,  nlevel = length(Breaks)-1)
            
            #	  axis(1, at = seq(0, 1, by = 0.2), labels = seq(0, nrows, by = nrows/5))
            #	  axis(2, at = seq(0, 1, by = 0.2), labels = seq(0, ncols, by = ncols/5))
            text(0.5, 0.98, labels = paste('week', i+month_shift), cex = 1)
            
            
          }
          
          
        }
      }
      
      dev.off()
      
    }
  }
}
  
  
  
  
  
}