wbt_*(): Pass through command_only argument to wbt_run_tool()

Author: brownag

PY2R/automation.py

@@ -67,7 +67,7 @@ def function_block(line, ff):
     start = line.find("(") + 1
     end = len(line) - 1
     argument = line[start:end]
-    function_head = "wbt_" + function_name + " <- function(" + argument + ") {"
+    function_head = "wbt_" + function_name + " <- function(" + argument + ", command_only=FALSE) {"
     ff.write(function_head + "\n")
     ff.write("  wbt_init()" + "\n")
     ff.write('  args <- ""' + "\n")
@@ -102,7 +102,7 @@ def function_block(line, ff):
 
     ff.write("  tool_name <- \""+function_name+"\"\n")
     # ff.write('  tool_name <- tool_name[!grepl("(whitebox|::)", tool_name)]' + "\n")
-    ff.write("  wbt_run_tool(tool_name, args, verbose_mode)" + "\n")
+    ff.write("  wbt_run_tool(tool_name, args, verbose_mode, command_only)" + "\n")
     ff.write("}" + "\n")
     ff.write("\n\n")
 

PY2R/scripts/data_tools.R

@@ -13,7 +13,7 @@
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_dbscan <- function(inputs, output, scaling="Normalize", search_dist=0.01, min_points=5, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_dbscan <- function(inputs, output, scaling="Normalize", search_dist=0.01, min_points=5, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -34,7 +34,7 @@ wbt_dbscan <- function(inputs, output, scaling="Normalize", search_dist=0.01, mi
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "dbscan"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -56,7 +56,7 @@ wbt_dbscan <- function(inputs, output, scaling="Normalize", search_dist=0.01, mi
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_k_means_clustering <- function(inputs, output, classes, out_html=NULL, max_iterations=10, class_change=2.0, initialize="diagonal", min_class_size=10, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_k_means_clustering <- function(inputs, output, classes, out_html=NULL, max_iterations=10, class_change=2.0, initialize="diagonal", min_class_size=10, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -84,7 +84,7 @@ wbt_k_means_clustering <- function(inputs, output, classes, out_html=NULL, max_i
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "k_means_clustering"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -106,7 +106,7 @@ wbt_k_means_clustering <- function(inputs, output, classes, out_html=NULL, max_i
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_knn_classification <- function(inputs, training, field, output, scaling="Normalize", k=5, clip=TRUE, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_knn_classification <- function(inputs, training, field, output, scaling="Normalize", k=5, clip=TRUE, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -132,7 +132,7 @@ wbt_knn_classification <- function(inputs, training, field, output, scaling="Nor
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "knn_classification"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -154,7 +154,7 @@ wbt_knn_classification <- function(inputs, training, field, output, scaling="Nor
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_knn_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, k=5, weight=TRUE, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_knn_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, k=5, weight=TRUE, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -182,7 +182,7 @@ wbt_knn_regression <- function(inputs, training, field, scaling="Normalize", out
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "knn_regression"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -202,7 +202,7 @@ wbt_knn_regression <- function(inputs, training, field, scaling="Normalize", out
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_logistic_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_logistic_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -224,7 +224,7 @@ wbt_logistic_regression <- function(inputs, training, field, scaling="Normalize"
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "logistic_regression"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -245,7 +245,7 @@ wbt_logistic_regression <- function(inputs, training, field, scaling="Normalize"
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_modified_k_means_clustering <- function(inputs, output, out_html=NULL, start_clusters=1000, merge_dist=NULL, max_iterations=10, class_change=2.0, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_modified_k_means_clustering <- function(inputs, output, out_html=NULL, start_clusters=1000, merge_dist=NULL, max_iterations=10, class_change=2.0, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -272,7 +272,7 @@ wbt_modified_k_means_clustering <- function(inputs, output, out_html=NULL, start
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "modified_k_means_clustering"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -295,7 +295,7 @@ wbt_modified_k_means_clustering <- function(inputs, output, out_html=NULL, start
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_random_forest_classification <- function(inputs, training, field, output=NULL, split_criterion="Gini", n_trees=500, min_samples_leaf=1, min_samples_split=2, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_random_forest_classification <- function(inputs, training, field, output=NULL, split_criterion="Gini", n_trees=500, min_samples_leaf=1, min_samples_split=2, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -326,7 +326,7 @@ wbt_random_forest_classification <- function(inputs, training, field, output=NUL
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "random_forest_classification"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -348,7 +348,7 @@ wbt_random_forest_classification <- function(inputs, training, field, output=NUL
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_random_forest_regression <- function(inputs, training, field, output=NULL, n_trees=100, min_samples_leaf=1, min_samples_split=2, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_random_forest_regression <- function(inputs, training, field, output=NULL, n_trees=100, min_samples_leaf=1, min_samples_split=2, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -376,7 +376,7 @@ wbt_random_forest_regression <- function(inputs, training, field, output=NULL, n
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "random_forest_regression"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -399,7 +399,7 @@ wbt_random_forest_regression <- function(inputs, training, field, output=NULL, n
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_svm_classification <- function(inputs, training, field, scaling="Normalize", output=NULL, c=200.0, gamma=50.0, tolerance=0.1, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_svm_classification <- function(inputs, training, field, scaling="Normalize", output=NULL, c=200.0, gamma=50.0, tolerance=0.1, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -430,7 +430,7 @@ wbt_svm_classification <- function(inputs, training, field, scaling="Normalize",
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "svm_classification"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }
 
 
@@ -453,7 +453,7 @@ wbt_svm_classification <- function(inputs, training, field, scaling="Normalize",
 #'
 #' @return Returns the tool text outputs.
 #' @export
-wbt_svm_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, c=50.0, eps=10.0, gamma=0.5, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE) {
+wbt_svm_regression <- function(inputs, training, field, scaling="Normalize", output=NULL, c=50.0, eps=10.0, gamma=0.5, test_proportion=0.2, wd=NULL, verbose_mode=FALSE, compress_rasters=FALSE, command_only=FALSE) {
   wbt_init()
   args <- ""
   args <- paste(args, paste0("--inputs=", wbt_file_path(inputs)))
@@ -484,7 +484,7 @@ wbt_svm_regression <- function(inputs, training, field, scaling="Normalize", out
     args <- paste(args, paste0("--compress_rasters=", compress_rasters))
   }
   tool_name <- "svm_regression"
-  wbt_run_tool(tool_name, args, verbose_mode)
+  wbt_run_tool(tool_name, args, verbose_mode, command_only)
 }