a required parameter can not have a default.

mlr-org · Jan 14, 2024 · 9c7fafd · 9c7fafd
1 parent f18628c
commit 9c7fafd
Show file tree

Hide file tree

Showing 12 changed files with 42 additions and 42 deletions.
diff --git a/R/LearnerClustAffinityPropagation.R b/R/LearnerClustAffinityPropagation.R
@@ -26,13 +26,13 @@ LearnerClustAP = R6Class("LearnerClustAP",
     initialize = function() {
       ps = ps(
         s = p_uty(tags = c("required", "train")),
-        p = p_uty(custom_check = function(x) {
+        p = p_uty(custom_check = crate(function(x) {
           if (test_numeric(x)) {
             return(TRUE)
           } else {
             stop("`p` needs to be a numeric vector")
           }
-        }, default = NA, tags = "train"),
+        }), default = NA, tags = "train"),
         q = p_dbl(lower = 0L, upper = 1L, tags = "train"),
         maxits = p_int(lower = 1L, default = 1000L, tags = "train"),
         convits = p_int(lower = 1L, default = 100L, tags = "train"),

diff --git a/R/LearnerClustAgnes.R b/R/LearnerClustAgnes.R
@@ -27,7 +27,7 @@ LearnerClustAgnes = R6Class("LearnerClustAgnes",
         method = p_fct(default = "average", levels = c("average", "single", "complete", "ward", "weighted", "flexible", "gaverage"), tags = "train"),
         trace.lev = p_int(lower = 0L, default = 0L, tags = "train"),
         k = p_int(lower = 1L, default = 2L, tags = "predict"),
-        par.method = p_uty(tags = "train", custom_check = function(x) {
+        par.method = p_uty(tags = "train", custom_check = crate(function(x) {
             if (test_numeric(x) || test_list(x)) {
               if (length(x) %in% c(1L, 3L, 4L)) {
                 return(TRUE)
@@ -36,7 +36,7 @@ LearnerClustAgnes = R6Class("LearnerClustAgnes",
             } else {
               stop("`par.method` needs to be a numeric vector")
             }
-          })
+          }))
       )
 
       # param deps

diff --git a/R/LearnerClustCMeans.R b/R/LearnerClustCMeans.R
@@ -23,24 +23,24 @@ LearnerClustCMeans = R6Class("LearnerClustCMeans",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        centers = p_uty(tags = c("required", "train"), default = 2L,
-          custom_check = function(x) {
+        centers = p_uty(tags = c("required", "train"),
+          custom_check = crate(function(x) {
             if (test_data_frame(x)) {
               return(TRUE)
             } else if (test_int(x)) {
               assert_true(x >= 1L)
             } else {
               return("`centers` must be integer or data.frame with initial cluster centers")
             }
-          }
+          })
         ),
         iter.max = p_int(lower = 1L, default = 100L, tags = "train"),
         verbose = p_lgl(default = FALSE, tags = "train"),
         dist = p_fct(levels = c("euclidean", "manhattan"), default = "euclidean", tags = "train"),
         method = p_fct(levels = c("cmeans", "ufcl"), default = "cmeans", tags = "train"),
         m = p_dbl(lower = 1L, default = 2L, tags = "train"),
         rate.par = p_dbl(lower = 0L, upper = 1L, tags = "train"),
-        weights = p_uty(default = 1L, custom_check = function(x) {
+        weights = p_uty(default = 1L, custom_check = crate(function(x) {
             if (test_numeric(x)) {
               if (sum(sign(x)) == length(x)) {
                 return(TRUE)
@@ -52,7 +52,7 @@ LearnerClustCMeans = R6Class("LearnerClustCMeans",
             } else {
               return("`weights` must be positive numeric vector or a single positive number")
             }
-          },
+          }),
           tags = "train"),
         control = p_uty(tags = "train")
       )

diff --git a/R/LearnerClustDBSCAN.R b/R/LearnerClustDBSCAN.R
@@ -24,13 +24,13 @@ LearnerClustDBSCAN = R6Class("LearnerClustDBSCAN",
         eps = p_dbl(lower = 0L, tags = c("required", "train")),
         minPts = p_int(lower = 0L, default = 5L, tags = "train"),
         borderPoints = p_lgl(default = TRUE, tags = "train"),
-        weights = p_uty(custom_check = function(x) {
+        weights = p_uty(custom_check = crate(function(x) {
           if (test_numeric(x)) {
             return(TRUE)
           } else {
             stop("`weights` need to be a numeric vector")
           }
-        }, tags = "train"),
+        }), tags = "train"),
         search = p_fct(levels = c("kdtree", "linear", "dist"), default = "kdtree", tags = "train"),
         bucketSize = p_int(lower = 1L, default = 10L, tags = "train"),
         splitRule = p_fct(levels = c("STD", "MIDPT", "FAIR", "SL_MIDPT", "SL_FAIR", "SUGGEST"), default = "SUGGEST", tags = "train"),

diff --git a/R/LearnerClustDBSCANfpc.R b/R/LearnerClustDBSCANfpc.R
@@ -24,24 +24,24 @@ LearnerClustDBSCANfpc = R6Class("LearnerClustDBSCANfpc",
         scale = p_lgl(default = FALSE, tags = "train"),
         method = p_fct(levels = c("hybrid", "raw", "dist"), tags = "train"),
         seeds = p_lgl(default = TRUE, tags = "train"),
-        showplot = p_uty(custom_check = function(x) {
+        showplot = p_uty(custom_check = crate(function(x) {
           if (test_flag(x)) {
             return(TRUE)
           } else if (test_int(x, lower = 0, upper = 2)) {
             return(TRUE)
           } else {
             stop("`showplot` need to be either logical or integer between 0 and 2")
           }
-        }, default = FALSE, tags = "train"),
-        countmode = p_uty(custom_check = function(x) {
+        }), default = FALSE, tags = "train"),
+        countmode = p_uty(custom_check = crate(function(x) {
           if (test_integer(x)) {
             return(TRUE)
           } else if (test_null(x)) {
             return(TRUE)
           } else {
             stop("`countmode` need to be NULL or vector of integers")
           }
-        }, default = NULL, tags = "train")
+        }), default = NULL, tags = "train")
       )
 
       param_set$values = list(MinPts = 5L, scale = FALSE, seeds = TRUE,

diff --git a/R/LearnerClustFanny.R b/R/LearnerClustFanny.R
@@ -25,7 +25,7 @@ LearnerClustFanny = R6Class("LearnerClustFanny",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        k = p_int(lower = 1L, default = 2L, tags = c("required", "train")),
+        k = p_int(lower = 1L, tags = c("required", "train")),
         memb.exp = p_dbl(lower = 1L, default = 2L, tags = "train"),
         metric = p_fct(default = "euclidean", levels = c("euclidean", "manhattan", "SqEuclidean"), tags = "train"),
         stand = p_lgl(default = FALSE, tags = "train"),

diff --git a/R/LearnerClustFeatureless.R b/R/LearnerClustFeatureless.R
@@ -19,7 +19,7 @@ LearnerClustFeatureless = R6Class("LearnerClustFeatureless",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        num_clusters = p_int(lower = 1L, default = 1L, tags = c("required", "train", "predict"))
+        num_clusters = p_int(lower = 1L, tags = c("required", "train", "predict"))
       )
       ps$values = list(num_clusters = 1L)
 

diff --git a/R/LearnerClustKKMeans.R b/R/LearnerClustKKMeans.R
@@ -24,16 +24,16 @@ LearnerClustKKMeans = R6Class("LearnerClustKKMeans",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        centers = p_uty(tags = c("required", "train"), default = 2L,
-          custom_check = function(x) {
+        centers = p_uty(tags = c("required", "train"),
+          custom_check = crate(function(x) {
             if (test_data_frame(x)) {
               return(TRUE)
             } else if (test_int(x)) {
               assert_true(x >= 1L)
             } else {
               return("`centers` must be integer or data.frame with initial cluster centers")
             }
-          }
+          })
         ),
         kernel = p_fct(default = "rbfdot",
           levels = c( "vanilladot", "polydot", "rbfdot", "tanhdot", "laplacedot", "besseldot", "anovadot", "splinedot"),

diff --git a/R/LearnerClustKMeans.R b/R/LearnerClustKMeans.R
@@ -23,16 +23,16 @@ LearnerClustKMeans = R6Class("LearnerClustKMeans",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        centers = p_uty(tags = c("required", "train"), default = 2L,
-          custom_check = function(x) {
+        centers = p_uty(tags = c("required", "train"),
+          custom_check = crate(function(x) {
             if (test_data_frame(x)) {
               return(TRUE)
             } else if (test_int(x)) {
               assert_true(x >= 1L)
             } else {
               return("`centers` must be integer or data.frame with initial cluster centers")
             }
-          }
+          })
         ),
         iter.max = p_int(lower = 1L, default = 10L, tags = c("train")),
         algorithm = p_fct(levels = c("Hartigan-Wong", "Lloyd", "Forgy", "MacQueen"), default = "Hartigan-Wong", tags = c("train")),

diff --git a/R/LearnerClustMclust.R b/R/LearnerClustMclust.R
@@ -21,48 +21,48 @@ LearnerClustMclust = R6Class("LearnerClustMclust",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        G = p_uty(default = c(1:9), custom_check = function(x) {
+        G = p_uty(default = c(1:9), custom_check = crate(function(x) {
           if (test_numeric(x)) {
             return(TRUE)
           } else {
             stop("`G` need to be a numeric vector")
           }
-        }, tags = "train"),
-        modelNames = p_uty(custom_check = function(x) {
+        }), tags = "train"),
+        modelNames = p_uty(custom_check = crate(function(x) {
           if (test_character(x)) {
             return(TRUE)
           } else {
             stop("`modelNames` need to be a character vector")
           }
-        }, tags = "train"),
-        prior = p_uty(custom_check = function(x) {
+        }), tags = "train"),
+        prior = p_uty(custom_check = crate(function(x) {
           if (test_list(x)) {
             return(TRUE)
           } else {
             stop("`prior` need to be a list")
           }
-        }, tags = "train"),
-        control = p_uty(default = mclust::emControl(), custom_check = function(x) {
+        }), tags = "train"),
+        control = p_uty(default = mclust::emControl(), custom_check = crate(function(x) {
           if (test_list(x)) {
             return(TRUE)
           } else {
             stop("`control` need to be a list of control parameters for EM")
           }
-        }, tags = "train"),
-        initialization = p_uty(custom_check = function(x) {
+        }), tags = "train"),
+        initialization = p_uty(custom_check = crate(function(x) {
           if (test_list(x)) {
             return(TRUE)
           } else {
             stop("`initialization` need to be a list of initialization components")
           }
-        }, tags = "train"),
-        x = p_uty(custom_check = function(x) {
+        }), tags = "train"),
+        x = p_uty(custom_check = crate(function(x) {
           if (test_class(x, "mclustBIC")) {
             return(TRUE)
           } else {
             stop("`x` need to be an object of class 'mclustBIC'")
           }
-        }, tags = "train")
+        }), tags = "train")
       )
 
       super$initialize(

diff --git a/R/LearnerClustMeanShift.R b/R/LearnerClustMeanShift.R
@@ -21,20 +21,20 @@ LearnerClustMeanShift = R6Class("LearnerClustMeanShift",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        h = p_uty(custom_check = function(x) {
+        h = p_uty(custom_check = crate(function(x) {
             if (test_numeric(x) || test_int(x)) {
               return(TRUE)
             } else {
               return("`h` must be either integer or numeric vector")
             }
-          }, tags = "train"),
-        subset = p_uty(custom_check = function(x) {
+          }), tags = "train"),
+        subset = p_uty(custom_check = crate(function(x) {
           if (test_numeric(x)) {
             return(TRUE)
           } else {
             return("`subset` must be a numeric vector")
           }
-        }, tags = "train"),
+        }), tags = "train"),
         scaled = p_int(lower = 0L, default = 1, tags = "train"),
         iter = p_int(lower = 1L, default = 200L, tags = "train"),
         thr = p_dbl(default = 0.01, tags = "train")

diff --git a/R/LearnerClustPAM.R b/R/LearnerClustPAM.R
@@ -24,18 +24,18 @@ LearnerClustPAM = R6Class("LearnerClustPAM",
     #' Creates a new instance of this [R6][R6::R6Class] class.
     initialize = function() {
       ps = ps(
-        k = p_int(lower = 1L, default = 2L, tags = c("required", "train")),
+        k = p_int(lower = 1L, tags = c("required", "train")),
         metric = p_fct(levels = c("euclidian", "manhattan"), tags = "train"),
         medoids = p_uty(default = NULL, tags = "train",
-          custom_check = function(x) {
+          custom_check = custom(function(x) {
             if (test_integerish(x)) {
               return(TRUE)
             } else if (test_null(x)) {
               return(TRUE)
             } else {
               stop("`medoids` needs to be either `NULL` or vector with row indices!")
             }
-          }
+          })
         ),
         stand = p_lgl(default = FALSE, tags = "train"),
         do.swap = p_lgl(default = TRUE, tags = "train"),