R/onesim_plot.R

In rucky151/shapp1: Scenario Analysis for Seed Health

#' Plot a graph of output for one parameter combinations
#'
#' This function simulates one parameter combination across nseasons once
#'
#' Updated 2018-08-23

#' This plot is generated by function \code{\link{onesim}}.
#'
#' @inheritParams onesim
#' @import RColorBrewer
#' @import KernSmooth
#' @importFrom  magrittr %>%
#' @importFrom  dplyr mutate
#' @import ggplot2
#' @importFrom grDevices colorRampPalette
#' @importFrom stats median quantile rnorm var
#' @keywords seed health
#' @examples
#' onesim_plot()
#' @export
#'
#'


onesim_plot <- function(pHSinit=0.8, Kx = 100, betax=0.02, wxtnormm=0.8, wxtnormsd=0.3, hx=1, mxtnormm=1,
                       mxtnormsd=0.1, axtnormm=1, axtnormsd=0.1, rx=0.1, zxtnormm=1, zxtnormsd= 0.1, gx=4,
                       cx=0.9, phix=0, nseasons=10, HPcut=0.5, pHScut=0.5, maY=100, miY=0, thetax=0.2,  Ex=0){

  out1 <- onesim(pHSinit = pHSinit, Kx = Kx, Ex = Ex, betax = betax, wxtnormm = wxtnormm, hx = hx, 
                 mxtnormm = mxtnormm, axtnormm = axtnormm, gx = gx, zxtnormm = zxtnormm, cx = cx, 
                 rx = rx, phix = phix, thetax = thetax, wxtnormsd = wxtnormsd, mxtnormsd = mxtnormsd, 
                 axtnormsd = axtnormsd, zxtnormsd = zxtnormsd, nseasons = nseasons, HPcut = HPcut, 
                 pHScut = pHScut, maY = maY, miY = miY)


  Yield_Loss <- out1$outm$YL[-1]
  Season <- out1$outm$season[-1]

  for(i in 1:100){ # higher values make a smoother plot
    out1<- onesim(pHSinit = pHSinit, Kx = Kx, Ex = Ex, betax = betax, wxtnormm = wxtnormm, hx = hx, 
                  mxtnormm = mxtnormm, axtnormm = axtnormm, gx = gx, zxtnormm = zxtnormm, cx = cx, 
                  rx = rx, phix = phix, thetax = thetax, wxtnormsd = wxtnormsd, mxtnormsd = mxtnormsd, 
                  axtnormsd = axtnormsd, zxtnormsd = zxtnormsd, nseasons = nseasons, HPcut = HPcut, 
                  pHScut = pHScut, maY = maY, miY = miY )

    Yield_Loss <- c(Yield_Loss,out1$outm$YL[-1])
    Season <- c(Season,out1$outm$season[-1])
  }
  #----------
  data <- as.data.frame(cbind(Yield_Loss,Season))
  data=data %>%
    mutate(SimulateCol = rep(1:(nrow(data)/nseasons), each=nseasons)) 

  ggplot(data, aes(Season, Yield_Loss)) +
    geom_point(alpha=0.1, color="dodgerblue") +
    geom_line(aes(group = data$SimulateCol), color="dodgerblue", alpha=0.1) +
    stat_summary() +
    stat_summary(geom="line") +
    theme_classic() +
    scale_x_continuous(breaks=1:10) +
    xlab('Season') +
    ylab('Yield Loss (%)') +
    theme(axis.title = element_text(face = "bold",
                                    size = 20),
          axis.text = element_text(size = 16),
          legend.background = element_blank(),
          #legend.box.background = element_blank(),
          panel.grid.major = element_blank(),
          panel.grid.minor = element_blank(),
          panel.background = element_rect(fill = "transparent",colour = NA),
          plot.background = element_rect(fill = "transparent",colour = NA)
    )
  #---------------------------------------------
  }