R/tictactoe.R
tictactoe.Rd
Construct a base tic-tac-toe plot for presenting predator-prey PSD values. Predator-prey PSD values are added with plotCI
from plotrix.
tictactoe(predobj = c(30, 70), preyobj = c(30, 70), predlab = "Predator PSD", preylab = "Prey PSD", obj.col = "black", obj.trans = 0.2, bnd.col = "black", bnd.lwd = 1, bnd.lty = 2)
predobj | A vector of length 2 that contains the target objective range for the predator. |
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preyobj | A vector of length 2 that contains the target objective range for the prey. |
predlab | A string representing a label for the x-axis. |
preylab | A string representing a label for the y-axis. |
obj.col | A string designating a color to which the target objective regions should be shaded. |
obj.trans | A numeric (decimal) that indicates the level of transparency for marking the target objective regions. |
bnd.col | A string that indicates a color for the boundaries of the target objective regions. |
bnd.lwd | A numeric that indicates the line width for the boundaries of the target objective regions. |
bnd.lty | A numeric that indicates the line type for the boundaries of the target objective regions. |
None. However, a graphic is produced.
This function simply creates a base tic-tac-toe plot. Observed values, with confidence intervals, are added to this plot with plotCI
from plotrix; see examples.
6-Size Structure.
Ogle, D.H. 2016. Introductory Fisheries Analyses with R. Chapman & Hall/CRC, Boca Raton, FL.
## Create hypothetical data for plotting one point .. similar to what might come from psdCalc() prey <- c(45.4,30.2,56.8) pred <- c(24.5,10.2,36.7) names(prey) <- names(pred) <- c("Estimate","95% LCI","95% UCI") prey#> Estimate 95% LCI 95% UCI #> 45.4 30.2 56.8pred#> Estimate 95% LCI 95% UCI #> 24.5 10.2 36.7tictactoe()if (require(plotrix)) { plotCI(prey[1],pred[1],li=prey[2],ui=prey[3],err="x",pch=16,add=TRUE) plotCI(prey[1],pred[1],li=pred[2],ui=pred[3],err="y",pch=16,add=TRUE) }#>## Create hypothetical data for plotting three points .. similar to what might come from psdCalc() prey <- rbind(c(45.4,30.2,56.8), c(68.2,56.7,79.4), c(17.1, 9.5,26.3)) pred <- rbind(c(24.5,10.2,36.7), c(14.2, 7.1,21.3), c(16.3, 8.2,24.4)) colnames(prey) <- colnames(pred) <- c("Estimate","95% LCI","95% UCI") prey#> Estimate 95% LCI 95% UCI #> [1,] 45.4 30.2 56.8 #> [2,] 68.2 56.7 79.4 #> [3,] 17.1 9.5 26.3pred#> Estimate 95% LCI 95% UCI #> [1,] 24.5 10.2 36.7 #> [2,] 14.2 7.1 21.3 #> [3,] 16.3 8.2 24.4tictactoe()if (require(plotrix)) { plotCI(prey[,1],pred[,1],li=prey[,2],ui=prey[,3],err="x",pch=16,add=TRUE) plotCI(prey[,1],pred[,1],li=pred[,2],ui=pred[,3],err="y",pch=16,add=TRUE) }lines(prey[,1],pred[,1])text(prey[,1],pred[,1],labels=c(2010,2011,2012),adj=c(-0.5,-0.5))