## ----------------------------------------------------------------------------- #| label: setup #| include: false # Nothing in this vignette is evaluated: it exists to show the shape of the # changes, not to fit models. knitr::opts_chunk$set(eval = FALSE) ## ----------------------------------------------------------------------------- # Before: models were returned unless you said otherwise results <- seqwrap(container, cores = 4) results@models[[1]] # Now: ask for them explicitly results <- seqwrap(container, return_models = TRUE, cores = 4) ## ----------------------------------------------------------------------------- # Before: a named list, indexed by target results@summaries[["ENSG00000141510"]] # Now: one data frame, filtered subset(results@summaries, target == "ENSG00000141510") ## ----------------------------------------------------------------------------- results <- seqwrap(container, cache = "disk", cores = 4) # Read and combine the cached chunks combined <- seqwrap_summarise(results) seqwrap_cache_clear(results) ## ----------------------------------------------------------------------------- # Before warned <- results@errors |> dplyr::filter(purrr::map_lgl(warnings_fit, ~ !is.null(.x[[1]]))) |> dplyr::pull(warnings_fit) # Now warned <- seqwrap_errors(results, stage = "fit", type = "warning") # Which warnings dominate warned |> dplyr::count(message, sort = TRUE) ## ----------------------------------------------------------------------------- results@targets # Targets that completed cleanly setdiff(results@targets, seqwrap_errors(results)$target) ## ----------------------------------------------------------------------------- combined <- seqwrap_summarise(results, drop_warnings = TRUE) combined$dropped ## ----------------------------------------------------------------------------- combined <- seqwrap_summarise(results) usable <- subset(combined$evaluations, converged & !singular) ## ----------------------------------------------------------------------------- results <- seqwrap(container, eval_fun = residual_diagnostics, cores = 4)