remove unicode

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: tidysdm
 Title: Species Distribution Models with Tidymodels
-Version: 0.9.1.9001
+Version: 0.9.2
 Authors@R: c(
     person("Michela", "Leonardi", role = "aut"),
     person("Margherita", "Colucci", role = "aut"),

NEWS.md

@@ -1,6 +1,6 @@
 # `tidysdm` 0.9.2
 
-* Clean up for CRAN
+* Release on CRAN
 
 # `tidysdm` 0.9.1
 

R/blockcv2rsample.R

@@ -16,7 +16,7 @@
 #'   k = 5, # number of folds
 #'   size = 350000, # size of the blocks in metres
 #'   selection = "random", # random blocks-to-fold
-#'   iteration = 50
+#'   iteration = 10
 #' ) # find evenly dispersed folds
 #' sb1_rsample <- blockcv2rsample(sb1, pa_data)
 #' class(sb1_rsample)

R/boyce_cont.R

@@ -12,11 +12,11 @@
 #' and estimate arguments, or a table/matrix where the true class
 #' results should be in the columns of the table.
 #' @param ... A set of unquoted column names or one or more dplyr selector functions to choose which variables contain the class probabilities. If truth is binary, only 1 column should be selected, and it should correspond to the value of event_level. Otherwise, there should be as many columns as factor levels of truth and the ordering of the columns should be the same as the factor levels of truth.
-#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, a factor vector.
+#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.
 #' @param estimator One of "binary", "hand_till", "macro", or "macro_weighted" to specify the type of averaging to be done. "binary" is only relevant for the two class case. The others are general methods for calculating multiclass metrics. The default will automatically choose "binary" if truth is binary, "hand_till" if truth has >2 levels and case_weights isn't specified, or "macro" if truth has >2 levels and case_weights is specified (in which case "hand_till" isn't well-defined).
 #' @param na_rm A logical value indicating whether NA values should be stripped before the computation proceeds.
 #' @param event_level A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default uses an internal helper that generally defaults to "first"
-#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For ⁠_vec()⁠ functions, a numeric vector.
+#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For _vec() functions, a numeric vector.
 #' @param estimate If truth is binary, a numeric vector of class probabilities corresponding to the "relevant" class. Otherwise, a matrix with as many columns as factor levels of truth. It is assumed that these are in the same order as the levels of truth.
 #' @returns A tibble with columns .metric, .estimator, and .estimate and 1 row of values.
 #' For grouped data frames, the number of rows returned will be the same as the

R/kap_max.R

@@ -13,11 +13,11 @@
 #' and estimate arguments, or a table/matrix where the true class
 #' results should be in the columns of the table.
 #' @param ... A set of unquoted column names or one or more dplyr selector functions to choose which variables contain the class probabilities. If truth is binary, only 1 column should be selected, and it should correspond to the value of event_level. Otherwise, there should be as many columns as factor levels of truth and the ordering of the columns should be the same as the factor levels of truth.
-#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, a factor vector.
+#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.
 #' @param estimator One of "binary", "hand_till", "macro", or "macro_weighted" to specify the type of averaging to be done. "binary" is only relevant for the two class case. The others are general methods for calculating multiclass metrics. The default will automatically choose "binary" if truth is binary, "hand_till" if truth has >2 levels and case_weights isn't specified, or "macro" if truth has >2 levels and case_weights is specified (in which case "hand_till" isn't well-defined).
 #' @param na_rm A logical value indicating whether NA values should be stripped before the computation proceeds.
 #' @param event_level A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default uses an internal helper that generally defaults to "first"
-#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For ⁠_vec()⁠ functions, a numeric vector.
+#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For _vec() functions, a numeric vector.
 #' @param estimate If truth is binary, a numeric vector of class probabilities corresponding to the "relevant" class. Otherwise, a matrix with as many columns as factor levels of truth. It is assumed that these are in the same order as the levels of truth.
 #' @returns A tibble with columns .metric, .estimator, and .estimate and 1 row of values.
 #' For grouped data frames, the number of rows returned will be the same as the

R/optim_thresh.R

@@ -6,7 +6,7 @@
 #' @param truth The column identifier for the true class results (that is a
 #' factor). This should be an unquoted column name although this argument is
 #' passed by expression and supports quasiquotation (you can unquote column
-#' names). For ⁠_vec()⁠ functions, a factor vector.
+#' names). For _vec() functions, a factor vector.
 #' @param estimate the predicted probability for the event
 #' @param metric character of metric to be optimised. Currently only "tss_max",
 #' "kap_max", and "sensitivity" with a given target

R/tss.R

@@ -14,11 +14,11 @@
 #' and estimate arguments, or a table/matrix where the true class
 #' results should be in the columns of the table.
 #' @param ... Not currently used.
-#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, a factor vector.
-#' @param estimate The column identifier for the predicted class results (that is also factor). As with truth this can be specified different ways but the primary method is to use an unquoted variable name. For ⁠_vec()⁠ functions, a factor vector.
+#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.
+#' @param estimate The column identifier for the predicted class results (that is also factor). As with truth this can be specified different ways but the primary method is to use an unquoted variable name. For _vec() functions, a factor vector.
 #' @param estimator One of: "binary", "macro", "macro_weighted", or "micro" to specify the type of averaging to be done. "binary" is only relevant for the two class case. The other three are general methods for calculating multiclass metrics. The default will automatically choose "binary" or "macro" based on estimate.
 #' @param na_rm A logical value indicating whether NA values should be stripped before the computation proceeds.
-#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For ⁠_vec()⁠ functions, a numeric vector.
+#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For _vec() functions, a numeric vector.
 #' @param event_level A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default is "first".
 #' @returns A tibble with columns .metric, .estimator, and .estimate and 1 row of values.
 #' For grouped data frames, the number of rows returned will be the same as the

R/tss_max.R

@@ -14,11 +14,11 @@
 #' and estimate arguments, or a table/matrix where the true class
 #' results should be in the columns of the table.
 #' @param ... A set of unquoted column names or one or more dplyr selector functions to choose which variables contain the class probabilities. If truth is binary, only 1 column should be selected, and it should correspond to the value of event_level. Otherwise, there should be as many columns as factor levels of truth and the ordering of the columns should be the same as the factor levels of truth.
-#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For ⁠_vec()⁠ functions, a factor vector.
+#' @param truth The column identifier for the true class results (that is a factor). This should be an unquoted column name although this argument is passed by expression and supports quasiquotation (you can unquote column names). For _vec() functions, a factor vector.
 #' @param estimator One of "binary", "hand_till", "macro", or "macro_weighted" to specify the type of averaging to be done. "binary" is only relevant for the two class case. The others are general methods for calculating multiclass metrics. The default will automatically choose "binary" if truth is binary, "hand_till" if truth has >2 levels and case_weights isn't specified, or "macro" if truth has >2 levels and case_weights is specified (in which case "hand_till" isn't well-defined).
 #' @param na_rm A logical value indicating whether NA values should be stripped before the computation proceeds.
 #' @param event_level A single string. Either "first" or "second" to specify which level of truth to consider as the "event". This argument is only applicable when estimator = "binary". The default uses an internal helper that generally defaults to "first"
-#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For ⁠_vec()⁠ functions, a numeric vector.
+#' @param case_weights The optional column identifier for case weights. This should be an unquoted column name that evaluates to a numeric column in data. For _vec() functions, a numeric vector.
 #' @param estimate If truth is binary, a numeric vector of class probabilities corresponding to the "relevant" class. Otherwise, a matrix with as many columns as factor levels of truth. It is assumed that these are in the same order as the levels of truth.
 #' @returns A tibble with columns .metric, .estimator, and .estimate and 1 row of values.
 #' For grouped data frames, the number of rows returned will be the same as the

cran_comments.md

@@ -0,0 +1,28 @@
+This is a new package not present on CRAN yet.
+
+On all testing environment (see below), we only get a note because of the
+package being a new submission, and a false positive for mispelling 
+(paleoclimate is an existing word and is spelled correctly).
+
+## Test environments
+- R-hub windows-x86_64-devel (r-devel)
+- R-hub ubuntu-gcc-release (r-release)
+- R-hub fedora-clang-devel (r-devel)
+- devtools::check_mac_release
+
+## R CMD check results
+On all systems:
+
+* checking CRAN incoming feasibility ... NOTE
+Maintainer: ‘Andrea Manica <[email protected]>’
+
+New submission
+
+Possibly misspelled words in DESCRIPTION:
+    Leonardi (9:6)
+    Tidymodels (2:41)
+    al (9:18)
+    et (9:15)
+    tidymodels (8:56)
+
+0 errors ✔ | 0 warnings ✔ | 1 notes ✖

data-raw/helper_functions/submitting_to_cran.R

@@ -7,6 +7,9 @@ urlchecker::url_check()
 
 # enhanced local checks
 devtools::check(remote = TRUE, manual = TRUE)
+# if unicode characters present and crashing latex
+# grep --color='auto' -P -n "[^\x00-\x7F]" -r * 
+
 
 source("./data-raw/helper_functions/check_returns_in_documentation.R")