data-raw/allowed_inputs_outputs.R

In dynverse/dynwrap: Representing and Inferring Single-Cell Trajectories

library(tidyverse)
devtools::load_all()

# # allowed outputs ---------------------------------------
#
# # all functions which start with an "add", but filtered by:
# # if they contain "The trajectory model." as return value in documentation
# # or if they are one of:
# output_ids_builds_upon_trajectory <- c("root", "pseudotime", "waypoints", "dimred", "grouping", "timings")
#
# requireNamespace("dynwrap")
# add_ids <- as.character(lsf.str(asNamespace("dynwrap"))) %>%
#   stringr::str_subset("^add_.*")
#
# requireNamespace("Rd2roxygen")
# allowed_outputs <- map_df(add_ids, function(add_id) {
#   print(add_id)
#
#   output_id <- gsub("add_(.*)", "\\1", add_id)
#
#   file <- paste0("man/", add_id, ".Rd")
#   rd <- Rd2roxygen::parse_file(file)
#
#   creates_trajectory <- str_detect(rd$value, ".*The trajectory model.*") && !is.null(rd$value)
#   builds_upon_trajectory <- output_id %in% output_ids_builds_upon_trajectory
#
#   processor <- get_output_processor(output_id)
#
#   # exception for trajectory
#   if (output_id == "trajectory") {
#     processor$required_args <- c(processor$required_args, "milestone_percentages", "progressions")
#     processor$optional_args <- processor$optional_args[!processor$optional_args %in% c("progressions", "milestone_percentages")]
#   }
#
#   if (creates_trajectory || builds_upon_trajectory) {
#     tibble(
#       output_id = output_id,
#       description = rd$title,
#       creates_trajectory = creates_trajectory,
#       required_args = list(processor$required_args),
#       optional_args = list(processor$optional_args)
#     )
#   } else {
#     tibble()
#   }
# })

# allowed inputs --------------------------------
# will use expression/counts and all priors EXCEPT dataset
data("priors", package = "dynwrap")

allowed_inputs <- tribble(
  ~input_id, ~description,
  "expression", "Expression matrix (sparse)",
  "counts", "Raw counts matrix (sparse)",
  "expression_future", "Future expression matrix based on RNA velocity (sparse)"
) %>% bind_rows(
  priors %>% select(input_id = prior_id, description = description)
)

usethis::use_data(allowed_outputs, allowed_inputs, overwrite = TRUE)