26 update plotting functionality within tcplfit2 r package

[gracezhihuizhao]

This PR includes:

• concRespPlot2: takes in concRespCore or tcplhit2_core output and plots the observed concentration response data with the winning model.
• plot_allcuvres: takes in tcplfit2_core output and plots the observed concentration response data along with all the model fits.
• A vignette showing how to use the plotting functionality and a few examples of how to add additional details to the basic plot (such as BMD, AC50, cutoff, etc.).

[gracezhihuizhao]

The plot_allcurves function errors if not all of the models are able to be fit. This should not occur - that is, at least display the models that do fit and throw a warning message with the models that are not included in the plot.

simulated experimental dose groups

X <- rep(seq(from = 0,to = 10,length.out = 10),each = 3)

Parameters

alpha <- (-17.31) beta <- (-11.54) beta_1 <- alpha/beta beta_2 <- alpha/(beta)^2

simulated experimental observed response data

set.seed(425) Y <- alpha*(X/beta +(X/beta)^2) + rt(df = 5,n = length(X))

true simulated curve

XC <- seq(from = 0,to = 10,length.out = 100) YC <- alpha*(XC/beta +(XC/beta)^2)

plot the simulated data

plot(X,Y,xlab = "dose",ylab = "response") abline(v = 0,h = 0,col = "red") abline(v = 5.77,col = "gray",lty = "dashed") lines(XC,YC,col = "black")

The plot_allcurves function now should be able to warn the user if any curves from the output failed and plot rest of the successful curve fits. Testing with your codes will result in this warning message and a plot of rest of the curves:

output <- tcplfit2_core(X, Y, cutoff=2) plot_allcurves(output, X, Y)