Minor updates to silence some annoying warnings

Author: mattwarkentin

R/predict.R

@@ -6,6 +6,7 @@
 #'   extraction before making model predictions.
 #'
 #' @param input Path to a CSV. See Details.
+#' @param quiet Logical. Set to `TRUE` to suppress messages. Default is `FALSE`.
 #'
 #' @details
 #' The input for this function should be a path to aCSV with the following
@@ -29,11 +30,11 @@
 #' @import glmnet parsnip recipes workflows vetiver readr
 #'
 #' @export
-predict_integral_radiomics <- function(input) {
-  df <- process_input_csv(input)
+predict_integral_radiomics <- function(input, quiet = FALSE) {
+  df <- process_input_csv(input, quiet)
 
   feats <-
-    purrr::map2(df$image, df$mask, extract_radiomics) |>
+    purrr::map2(df$image, df$mask, extract_radiomics, .progress = !quiet) |>
     purrr::list_rbind()
 
   pred_df <- dplyr::bind_cols(df, feats)
@@ -46,7 +47,12 @@ predict_integral_radiomics <- function(input) {
   pred <- stats::predict(model, new_data = pred_df, type = "prob")
 
   dplyr::bind_cols(df, pred) |>
-    dplyr::select(-c(study, pid, nid))
+    dplyr::select(-c(study, pid, nid)) |>
+    dplyr::rename_with(\(x) stringr::str_remove(x, "^epi_")) |>
+    dplyr::rename(
+      pred_benign = .pred_0,
+      pred_malignant = .pred_1
+    )
 }
 
-utils::globalVariables(c("study", "pid", "nid"))
+utils::globalVariables(c("study", "pid", "nid", ".pred_0", ".pred_1"))

R/process_input_csv.R

@@ -1,5 +1,5 @@
-process_input_csv <- function(input) {
-  df <- readr::read_csv(input)
+process_input_csv <- function(input, quiet) {
+  df <- readr::read_csv(input, show_col_types = !quiet, progress = !quiet)
 
   image <- check_files_exist(df$image, "`image`")
   mask <- check_files_exist(df$mask, "`mask`")

R/radiomics-extraction.R

@@ -2,12 +2,18 @@
 #'
 #' @param image File path to input image.
 #' @param mask File path to nodule mask.
+#' @param quiet Logical. Set to `TRUE` to suppress messages. Default is `FALSE`.
 #'
 #' @export
-extract_radiomics <- function(image, mask) {
+extract_radiomics <- function(image, mask, quiet = FALSE) {
   params <- system.file("PyRadiomics_config.yaml", package = "integralrad")
   extractor <- radiomics$featureextractor$RadiomicsFeatureExtractor(params)
+
+  logger <- logging$getLogger("radiomics.glcm")
+  logger$setLevel(logging$ERROR)
+
   result <- extractor$execute(image, mask)
+
   names_to_remove <- stringr::str_detect(names(result), "^diagnostics_")
   results_tbl <- dplyr::as_tibble(result[!names_to_remove])
   results_tbl

R/zzz.R

@@ -1,4 +1,5 @@
 radiomics <- NULL
+logging <- NULL
 
 .onLoad <- function(libname, pkgname) {
   Sys.setenv(RETICULATE_PYTHON = "managed")
@@ -9,6 +10,6 @@ radiomics <- NULL
       "trimesh==3.23.5"
     )
   )
-
+  logging <<- reticulate::import("logging", delay_load = TRUE)
   radiomics <<- reticulate::import("radiomics", delay_load = TRUE)
 }

exec/INTEGRAL-Radiomics.R

@@ -16,6 +16,10 @@ input <- NA
 #| negative_alias: false
 output <- NA
 
-df_pred <- integralrad::predict_integral_radiomics(input)
+#| description: Suppress messages.
+#| negative_alias: false
+quiet <- FALSE
+
+df_pred <- integralrad::predict_integral_radiomics(input, quiet)
 
 readr::write_csv(df_pred, output)