Move functions for finding args to /man/rmd, redocument

Author: juliasilge

NAMESPACE

@@ -100,7 +100,6 @@ export(boost_tree)
 export(check_empty_ellipse)
 export(check_final_param)
 export(control_parsnip)
-export(convert_args)
 export(convert_stan_interval)
 export(decision_tree)
 export(eval_args)

R/aaa.R

@@ -30,56 +30,6 @@ convert_stan_interval <- function(x, level = 0.95, lower = TRUE) {
   res
 }
 
-#' Find args for documentation
-#' @rdname convert_args
-#' @keywords internal
-#' @export
-convert_args <- function(model_name) {
-  envir <- get_model_env()
-
-  args <-
-    ls(envir) %>%
-    tibble::tibble(name = .) %>%
-    dplyr::filter(grepl("args", name)) %>%
-    dplyr::mutate(model = sub("_args", "", name),
-                  args  = purrr::map(name, ~envir[[.x]])) %>%
-    dplyr::filter(grepl(model_name, model)) %>%
-    tidyr::unnest(args) %>%
-    dplyr::select(model:original) %>%
-    full_join(get_arg_defaults(model_name),
-              by = c("model", "engine", "parsnip", "original")) %>%
-    mutate(original = dplyr::if_else(!is.na(default),
-                                     paste0(original, " (", default, ")"),
-                                     original)) %>%
-    select(-default)
-
-  convert_df <- args %>%
-    dplyr::select(-model) %>%
-    tidyr::pivot_wider(names_from = engine, values_from = original)
-
-  convert_df %>%
-    knitr::kable(col.names = paste0("**", colnames(convert_df), "**"))
-
-}
-
-#' @rdname convert_args
-#' @keywords internal
-#' @export
-get_arg_defaults <- function(model) {
-  check_model_exists(model)
-  gdf <- get(paste0("get_defaults_", model))
-  gdf()
-}
-
-#' @rdname convert_args
-#' @keywords internal
-#' @export
-get_arg <- function(ns, f, arg) {
-  args <- formals(getFromNamespace(f, ns))
-  args <- as.list(args)
-  as.character(args[[arg]])
-}
-
 # ------------------------------------------------------------------------------
 # nocov
 

man/boost_tree.Rd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below:
 
 ## xgboost
@@ -76,7 +79,7 @@ get_defaults_boost_tree <- function() {
 
   )
 }
-parsnip::convert_args("boost_tree")
+convert_args("boost_tree")
 ```
 
 For spark, the default `mtry` is the square root of the number of predictors for classification, and one-third of the predictors for regression.

man/convert_args.Rd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below:
 
 ## rpart
@@ -66,6 +69,6 @@ get_defaults_decision_tree <- function() {
     "decision_tree", "spark",           "min_n", "min_instances_per_node", get_arg("sparklyr", "ml_decision_tree", "min_instances_per_node"),
   )
 }
-parsnip::convert_args("decision_tree")
+convert_args("decision_tree")
 ```
 

man/rmd/boost-tree.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below.
 
 ## lm
@@ -82,6 +85,6 @@ get_defaults_linear_reg <- function() {
     "linear_reg",  "keras",     "penalty",            "penalty",  get_arg("parsnip", "keras_mlp", "penalty"),
   )
 }
-parsnip::convert_args("linear_reg")
+convert_args("linear_reg")
 ```
 

man/rmd/decision-tree.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below.
 
@@ -83,6 +86,6 @@ get_defaults_logistic_reg <- function() {
     "logistic_reg",  "keras",     "penalty",            "penalty",  get_arg("parsnip", "keras_mlp", "penalty"),
   )
 }
-parsnip::convert_args("logistic_reg")
+convert_args("logistic_reg")
 ```
 

man/rmd/linear-reg.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below.
 
@@ -37,6 +40,6 @@ get_defaults_mars <- function() {
     "mars",  "earth",     "prune_method",  "pmethod",  get_arg("earth", "earth.fit", "pmethod")[2]
   )
 }
-parsnip::convert_args("mars")
+convert_args("mars")
 ```
 

man/rmd/logistic-reg.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below:
 
@@ -57,6 +60,6 @@ get_defaults_mlp <- function() {
     "mlp",   "nnet",   "epochs",          "maxit",         get_arg("nnet", "nnet.default", "maxit"),
   )
 }
-parsnip::convert_args("mlp")
+convert_args("mlp")
 ```
 

man/rmd/mars.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below.
 
@@ -66,6 +69,6 @@ get_defaults_multinom_reg <- function() {
     "multinom_reg",  "nnet",      "penalty",            "decay",    get_arg("nnet", "nnet.default", "decay"),
   )
 }
-parsnip::convert_args("multinom_reg")
+convert_args("multinom_reg")
 ```
 

man/rmd/mlp.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below:
 
 ## kknn
@@ -38,6 +41,6 @@ get_defaults_nearest_neighbor <- function() {
     "nearest_neighbor", "kknn",  "dist_power",    "distance", get_arg("kknn", "train.kknn", "distance"),
   )
 }
-parsnip::convert_args("nearest_neighbor")
+convert_args("nearest_neighbor")
 ```
 

man/rmd/multinom-reg.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below:
 
@@ -83,7 +86,7 @@ get_defaults_rand_forest <- function() {
     "rand_forest",  "spark",          "min_n",    "min_instances_per_node",   get_arg("sparklyr", "ml_random_forest", "min_instances_per_node"),
   )
 }
-parsnip::convert_args("rand_forest")
+convert_args("rand_forest")
 ```
 
 - For randomForest and spark, the default `mtry` is the square root of the number of predictors for classification, and one-third of the predictors for regression.

man/rmd/nearest-neighbor.Rmd

@@ -0,0 +1,42 @@
+```{r, include = FALSE}
+convert_args <- function(model_name) {
+  envir <- get_model_env()
+
+  args <-
+    ls(envir) %>%
+    tibble::tibble(name = .) %>%
+    dplyr::filter(grepl("args", name)) %>%
+    dplyr::mutate(model = sub("_args", "", name),
+                  args  = purrr::map(name, ~envir[[.x]])) %>%
+    dplyr::filter(grepl(model_name, model)) %>%
+    tidyr::unnest(args) %>%
+    dplyr::select(model:original) %>%
+    full_join(get_arg_defaults(model_name),
+              by = c("model", "engine", "parsnip", "original")) %>%
+    mutate(original = dplyr::if_else(!is.na(default),
+                                     paste0(original, " (", default, ")"),
+                                     original)) %>%
+    select(-default)
+
+  convert_df <- args %>%
+    dplyr::select(-model) %>%
+    tidyr::pivot_wider(names_from = engine, values_from = original)
+
+  convert_df %>%
+    knitr::kable(col.names = paste0("**", colnames(convert_df), "**"))
+
+}
+
+get_arg_defaults <- function(model) {
+  check_model_exists(model)
+  gdf <- get(paste0("get_defaults_", model))
+  gdf()
+}
+
+get_arg <- function(ns, f, arg) {
+  args <- formals(getFromNamespace(f, ns))
+  args <- as.list(args)
+  as.character(args[[arg]])
+}
+
+```

man/rmd/rand-forest.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. For this type of model, the template of the fit calls are below.
 
 ## flexsurv
@@ -37,6 +40,6 @@ get_defaults_surv_reg <- function() {
     "surv_reg",  "survival",  "dist",       "dist",     NA,
   )
 }
-parsnip::convert_args("surv_reg")
+convert_args("surv_reg")
 ```
 

man/rmd/setup.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below:
 
@@ -36,6 +39,6 @@ get_defaults_svm_poly <- function() {
     "svm_poly", "kernlab",  "margin",        "epsilon",  "0.1",
   )
 }
-parsnip::convert_args("svm_poly")
+convert_args("svm_poly")
 ```
 

man/rmd/surv-reg.Rmd

@@ -1,5 +1,8 @@
 # Engine Details
 
+```{r, child = "setup.Rmd", include = FALSE}
+```
+
 Engines may have pre-set default arguments when executing the model fit call. 
 For this type of model, the template of the fit calls are below:
 
@@ -63,6 +66,6 @@ get_defaults_svm_rbf <- function() {
     "svm_rbf", "liquidSVM",  "rbf_sigma",     "gammas",   "varies",
   )
 }
-parsnip::convert_args("svm_rbf")
+convert_args("svm_rbf")
 ```