Merge pull request #366 from sjevelazco/min_gub

new message in esm_ family function
sjevelazco · Feb 5, 2024 · 552311c · 552311c
2 parents 5d5e98d + b1a76f1
commit 552311c
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diff --git a/R/esm_gam.R b/R/esm_gam.R
@@ -143,6 +143,11 @@ esm_gam <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%

diff --git a/R/esm_gau.R b/R/esm_gau.R
@@ -97,6 +97,11 @@ esm_gau <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%

diff --git a/R/esm_gbm.R b/R/esm_gbm.R
@@ -112,6 +112,12 @@ esm_gbm <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   if (is.null(n_minobsinnode)) {
     n_minobsinnode <- as.integer(nrow(data) * 0.5 / 4)
   }

diff --git a/R/esm_glm.R b/R/esm_glm.R
@@ -104,6 +104,11 @@ esm_glm <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%

diff --git a/R/esm_max.R b/R/esm_max.R
@@ -142,6 +142,11 @@ esm_max <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%

diff --git a/R/esm_net.R b/R/esm_net.R
@@ -99,6 +99,11 @@ esm_net <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%

diff --git a/R/esm_svm.R b/R/esm_svm.R
@@ -105,6 +105,11 @@ esm_svm <- function(data,
   . <- part <- model <- TPR <- IMAE <- rnames <- thr_value <- n_presences <- n_absences <- AUC_mean <- pr_ab <- NULL
   variables <- dplyr::bind_rows(c(c = predictors))
 
+  # N of predictor requirement
+  if (length(predictors) <= 2) {
+    stop("The 'esm_' family function should be used to build models with more than 2 predictors, use the 'fit_' or 'tune_' family functions instead")
+  }
+
   # Formula
   formula1 <- utils::combn(variables, 2)
   nms <- apply(utils::combn(variables, 2), 2, function(x) paste(x, collapse = "_")) %>%