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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,53 +1,111 @@ | ||
| plot.estMod <- function ( | ||
| plot.modelFits <- function ( | ||
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| est_mod | ||
| # dose_levels | ||
| # posteriors = posterior_linear[[2]] | ||
| model_fits, | ||
| CrI = FALSE, | ||
| gAIC = TRUE, | ||
| avg_fit = TRUE | ||
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| ) { | ||
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| model <- est_mod$model | ||
| theta <- est_mod$fit$solution | ||
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| dose <- seq(min(dose_levels), max(dose_levels), length.out = 1e3) | ||
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| switch(model, | ||
| "emax" = { | ||
| resp_expr <- quote(theta[1] + (theta[2] * dose) / (theta[3] + dose))}, | ||
| "sigEmax" = { | ||
| resp_expr <- quote(theta[1] + (theta[2] * dose^theta[4]) / (theta[3]^theta[4] + dose^theta[4]))}, | ||
| "exponential" = { | ||
| resp_expr <- quote(theta[1] + theta[2] * (exp(dose / theta[3]) - 1))}, | ||
| "quadratic" = { | ||
| resp_expr <- quote(theta[1] + theta[2] * dose + theta[3] * dose^2)}, | ||
| "linear" = { | ||
| resp_expr <- quote(theta[1] + theta[2] * dose)}, | ||
| "logistic" = { | ||
| resp_expr <- quote(theta[1] + theta[2] / (1 + exp((theta[3] - dose) / theta[4])))}, | ||
| { | ||
| stop(GENERAL$ERROR$MODEL_OPTIONS)} | ||
| ) | ||
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| df <- data.frame(dose = dose, response = eval(resp_expr)) | ||
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| data.frame(dose = dose_levels, obs = ) | ||
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| plt <- ggplot2::ggplot(data = df) + | ||
| ggplot2::geom_line(ggplot2::aes(dose, response)) + | ||
| ggplot2::geom_point() | ||
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| return(plt) | ||
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| } | ||
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| plot.estMods <- function ( | ||
| plot_resolution <- 1e3 | ||
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| dose_levels <- model_fits[[1]]$dose_levels | ||
| post_summary <- summary.postList(attr(model_fits, "posterior")) | ||
| doses <- seq(from = min(dose_levels), | ||
| to = max(dose_levels), length.out = plot_resolution) | ||
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| preds_models <- sapply(model_fits, predictModelFit, doses = doses) | ||
| model_names <- names(model_fits) | ||
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| if (avg_fit) { | ||
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| mod_weigts <- sapply(model_fits, function (x) x$model_weight) | ||
| avg_mod <- preds_models %*% mod_weigts | ||
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| preds_models <- cbind(preds_models, avg_mod) | ||
| model_names <- c(model_names, "averageModel") | ||
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| est_mods | ||
| } | ||
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| ) { | ||
| gg_data <- data.frame( | ||
| dose_levels = rep(doses, length(model_names)), | ||
| fits = as.vector(preds_models), | ||
| models = rep(factor(model_names, | ||
| levels = c("linear", "emax", "exponential", | ||
| "sigEmax", "logistic", "quadratic", | ||
| "averageModel")), | ||
| each = plot_resolution)) | ||
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| plts <- lapply(est_mods, plot) | ||
| if (gAIC) { | ||
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| g_AICs <- sapply(model_fits, function (x) x$gAIC) | ||
| label_gAUC <- paste("AIC:", round(g_AICs, digits = 1)) | ||
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| if (avg_fit) { | ||
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| mod_weigts <- sort(mod_weigts, decreasing = TRUE) | ||
| paste_names <- names(mod_weigts) |> | ||
| gsub("exponential", "exp", x = _) |> | ||
| gsub("quadratic", "quad", x = _) |> | ||
| gsub("linear", "lin", x = _) |> | ||
| gsub("logistic", "log", x = _) |> | ||
| gsub("sigEmax", "sigE", x = _) | ||
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| label_avg <- paste0(paste_names, "=", round(mod_weigts, 1), | ||
| collapse = ", ") | ||
| label_gAUC <- c(label_gAUC, label_avg) | ||
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| } | ||
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| } | ||
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| plts <- ggplot2::ggplot() + | ||
| ## Layout etc. | ||
| ggplot2::theme_bw() + | ||
| ggplot2::labs(x = "Dose", | ||
| y = "Model Fits") + | ||
| ggplot2::theme(panel.grid.major = ggplot2::element_blank(), | ||
| panel.grid.minor = ggplot2::element_blank()) + | ||
| ## gAIC | ||
| {if (gAIC) { | ||
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| ggplot2::geom_text( | ||
| data = data.frame( | ||
| models = unique(gg_data$models), | ||
| label = label_gAUC), | ||
| mapping = ggplot2::aes(label = label_gAUC), | ||
| x = -Inf, y = Inf, hjust = "inward", vjust = "inward", | ||
| size = 3) | ||
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| } | ||
| } + | ||
| ## Posterior Credible Intervals | ||
| {if (CrI) { | ||
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| ggplot2::geom_errorbar( | ||
| data = data.frame(x = dose_levels, | ||
| ymin = post_summary[, 3], | ||
| ymax = post_summary[, 5]), | ||
| mapping = ggplot2::aes(x = x, | ||
| ymin = ymin, | ||
| ymax = ymax), | ||
| width = 0, alpha = 0.5) | ||
|
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| } | ||
| } + | ||
| ## Posterior Medians | ||
| ggplot2::geom_point( | ||
| data = data.frame(dose_levels = dose_levels, | ||
| fits = post_summary[, 4]), | ||
| mapping = ggplot2::aes(dose_levels, fits), | ||
| size = 2) + | ||
| ## Fitted Models | ||
| ggplot2::geom_line( | ||
| data = gg_data, | ||
| mapping = ggplot2::aes(dose_levels, fits)) + | ||
| ## Faceting | ||
| ggplot2::facet_wrap(~ models) | ||
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| return (plts) | ||
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| } | ||
| } |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,2 @@ | ||
| *.html | ||
| *.R |
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