jbplot_ensemble: jbplot_ensemble()

In jabbamodel/JABBA: Just Another Bayesian Biomass Assessment

jbplot_ensemble()

Description

Plots plots JABBA ensemble models + projections - joint or by run

Usage

jbplot_ensemble(
  kb,
  subplots = 1:6,
  joint = FALSE,
  plotCIs = TRUE,
  quantiles = c(0.025, 0.975),
  bfrac = 0.5,
  bref = c("bmsy", "b0")[1],
  reflines = TRUE,
  kbout = FALSE,
  ylabs = NULL,
  ylab.bref = NULL,
  plot = TRUE,
  as.png = FALSE,
  col = NULL,
  bref.col = "red",
  pch = NULL,
  lty = 1,
  lwd = 1.5,
  tickEndYr = FALSE,
  xlim = NULL,
  ylimAdj = 1.05,
  xaxs = "i",
  yaxs = "i",
  xylabs = TRUE,
  type = "l",
  legend = TRUE,
  legendlabels = "default",
  legend.loc = "topright",
  legendorder = "default",
  legendncol = 1,
  legendcex = 0.7,
  legendsp = 0.8,
  pwidth = 6.5,
  pheight = 5,
  punits = "in",
  res = 300,
  ptsize = 10,
  cex.main = 1,
  plotdir = NULL,
  filenameprefix = "",
  par = list(mar = c(5, 4, 1, 1) + 0.1),
  verbose = FALSE,
  shadecol = NULL,
  shadealpha = 0.3,
  new = TRUE,
  add = FALSE,
  single.plots = add,
  run = NULL,
  fmax = 5
)

Arguments

kb	objects from fit_jabba(),jabba_fw(), list of fit_jabba() or fit_jabba()$kbtrj
subplots	option choose from subplots 1:7 1: stock (B/Bmsy) 2: harvest (F/Fmsy) 3: B (Biomass) 4: H (Harvest rate) 5: Bdev (Process Deviations) 6: Catch 7: BB0 (B/K) 8: BBfrac
joint	if true it creates a joint ensemble from list of fit_jabba()
plotCIs	Plot Credibilty Interval
quantiles	default is 95CIs as c(0.025,0.975)
bfrac	biomass fraction of Bmsy or B0 (subplot 8), default 0.5Bmsy
bref	biomass fraction reference options c("bmsy","b0")
reflines	if TRUE show reference point lines in absolute plots
kbout	if TRUE, produces the kb data.frame as output
ylabs	yaxis labels for quants
ylab.bref	option to only specify BBfrac plot ylab final year of values to show for each model. By default it is set to the
col	Optional vector of colors to be used for lines. Input NULL
bref.col	option to set color for Bref reference line (default is "red")
pch	Optional vector of plot character values
lty	Optional vector of line types
lwd	Optional vector of line widths
tickEndYr	TRUE/FALSE switch to turn on/off extra axis mark at final year in timeseries plots.
xlim	= NULL range of years
ylimAdj	Multiplier for ylim parameter. Allows additional white space
xaxs	Choice of xaxs parameter (see ?par for more info)
yaxs	Choice of yaxs parameter (see ?par for more info)
type	Type parameter passed to points (default 'o' overplots points on top of lines)
legend	Add a legend?
legendlabels	Optional vector of labels to include in legend.
legend.loc	Location of legend. Either a string like "topleft" or a vector of two numeric values representing the fraction of the maximum in the x and y dimensions, respectively. See ?legend for more info on the string options.
legendorder	Optional vector of model numbers that can be used to have the legend display the model names in an order that is different than that which is represented in the summary input object.
legendncol	Number of columns for the legend.
legendsp	Space between legend labels
pwidth	Width of plot
pheight	Height of plot
punits	Units for PNG file
res	Resolution for PNG file
ptsize	Point size for PNG file
cex.main	Character expansion for plot titles
plotdir	Directory where PNG or PDF files will be written. By default it will be the directory where the model was run.
filenameprefix	Additional text to append to PNG or PDF file names. It will be separated from default name by an underscore.
par	list of graphics parameter values passed to par() function
verbose	Report progress to R GUI?
shadecol	uncertainty shading of hcxval horizon
shadealpha	Transparency adjustment used to make default shadecol
new	Create new empty plot window
add	surpresses par() to create multiplot figs
run	name for single models or joint ensembles
legendcex=1	Allows to adjust legend cex

Author(s)

Mostly adopted from ss3diags::SSplotEnsemble

Examples

data(iccat)
bet = iccat$bet 
# Fit Fox and Schaefer
jb1 <- build_jabba(catch=bet$catch,cpue=bet$cpue,se=bet$se,scenario = "Fox",model.type="Fox")
jb2 <- build_jabba(catch=bet$catch,cpue=bet$cpue,se=bet$se,scenario = "Schaefer",model.type="Schaefer")
fit1 = fit_jabba(jb1,quickmcmc=TRUE,verbose=TRUE)
fit2 = fit_jabba(jb2,quickmcmc=TRUE,verbose=TRUE)
# Compare
jbplot_ensemble(list(fit1,fit2))
# Joint to 2-model ensemble
jbplot_ensemble(list(fit1,fit2),joint=T)
# Do 2-model ensemble forecast
prj = fw_jabba(list(fit1),quant="Catch",type="abs",imp.values = seq(60,100,1)*1000)
jbplot_ensemble(prj)
# Zoom in
jbplot_ensemble(prj,xlim=c(2000,2027))

jabbamodel/JABBA documentation built on Nov. 2, 2024, 12:50 p.m.