## ----setup, include = FALSE--------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>", fig.align = "center", fig.width = 8, fig.height = 6, dpi = 110 ) ## ----setup-pkg---------------------------------------------------------------- library(janusplot) library(ggplot2) janusplot_shape_sensitivity_shapes() ## ----demo-data---------------------------------------------------------------- data("shape_sensitivity_demo") str(shape_sensitivity_demo, vec.len = 2) ## ----recovery-curves---------------------------------------------------------- janusplot_shape_sensitivity_plot(shape_sensitivity_demo, "recovery_curves") ## ----archetype-confusion, fig.width = 6, fig.height = 5----------------------- janusplot_shape_sensitivity_plot(shape_sensitivity_demo, "confusion_archetype") ## ----accuracy-grid------------------------------------------------------------ janusplot_shape_sensitivity_plot(shape_sensitivity_demo, "accuracy_grid") ## ----summary------------------------------------------------------------------ head(janusplot_shape_sensitivity_summary(shape_sensitivity_demo, level = "archetype"), 10) ## ----full-sweep, eval = FALSE------------------------------------------------- # # Configure parallel execution (optional) — you control the plan. # future::plan(future::multisession, workers = 4L) # # res <- janusplot_shape_sensitivity(parallel = TRUE) # # # Save for your paper # saveRDS(res, "shape_sensitivity_full.rds") # janusplot_shape_sensitivity_plot(res, "recovery_curves") ## ----custom-subset, eval = FALSE---------------------------------------------- # strict <- janusplot_shape_cutoffs(mono_strong = 0.95, curv_low = 0.1) # # res_strict <- janusplot_shape_sensitivity( # shapes = c("wave", "bimodal", "bi_wave"), # n_grid = c(200L, 500L), # sigma_grid = c(0.05, 0.10, 0.20), # n_rep = 100L, # cutoffs = strict # ) # # janusplot_shape_sensitivity_summary(res_strict, level = "fine") ## ----session-info------------------------------------------------------------- sessionInfo()