v10.8.0 release

README.md

@@ -170,6 +170,15 @@ Gitlab developers
 
 ## WHAT'S NEW IN
 
+### v10.8.0
+
+1) fun_check() and fun_info() removed from this repo and transferred into the cute package
+
+2) Warning: fun_check() must be conveted into cute::check() in all the functions of this repo
+
+3) Warning: fun_info() must be conveted into cute::info() in all the functions of this repo
+
+
 ### v10.7.0
 
 1) fun_gg_boxplot : name of arguments stat.disp and stat.disp.mean changed to stat.pos and stat.mean

dev/TODO.txt

+
+
+20210616
+
+Hello.
+
+
+J'ai créé un nouveau repo:
+git@gitlab.pasteur.fr:gmillot/cute.git
+que vous pouvez cloner en local:
+git clone git@gitlab.pasteur.fr:gmillot/cute.git
+
+Ensuite vous pourrez travailler dessus et puis vous effectuerez des demandes de merge auprès 
+de moi pour que j'incorpore votre travail.
+
+L'idée est que ce repo soit rapidement converti en package.
+On peut commencer avec une seule fonction provenant de l'ancien repo de dev cute_little_r_function
+et ensuite incorporer petit à petit les fonctions cleanées de cute_little_r_function
+
+Pour demain je vois 5 axes :
+1) piger le passage en package / le faire sur le repo cute et noter la procédure pour les autres
+2) Piger / créer les pages web de docu
+3) poursuivre les feuilles d'exemple
+4) tester les fonctions et basculer sur cute
+5) updater fun_gg_scatter
+
+A voir ce qui plait à qui.
+
+A demain
+
+
+20210301
 L'investissement dans le projet Cute:
 1) Terminer les pages d'exemple de chaque fonction (c'est long)
 2) Checker les functions existantes (les utiliser, les challenger)

examples_fun_check.R

-
-
-######## fun_check() #### check class, type, length, etc., of objects
-
-### Datasets
-vec1 <- -1:3 # vector of integers
-vec2 <- 1:3 / 3 # vector of proportions
-vec3 <- c(1, 2, 3) # vector of integers but stored as "double"
-vec4 <- "pearson" # vector of characters
-vec5 <- c("a", "b","a", "b") # vector of characters
-mat1 <- matrix(vec1) # matrix of integers
-mat2 <- matrix(c(1:3 / 3, NA)) # matrix of proportions with NA
-
-
-### Datasets info
-vec1 # vector of integers
-vec2 # vector of proportions
-vec3 # vector of integers but stored as "double"
-vec4 # vector of characters
-vec5 # vector of characters
-mat1 # matrix of integers
-mat2 # matrix of proportions with NA
-
-
-### Simple examples
-# Check that vec1 is of class integer (means that it is also a vector) -> ok
-fun_check(data = vec1, class = "integer")
-# Check that vec1 is a numeric vector -> error because vec1 is a vector of integers
-fun_check(data = vec1, class = "numeric")
-# Check that vec1 is an integer vector of length 3 without negative values and without NA -> error because of length 5 and negative values inside vec1
-fun_check(data = vec1, class = "vector", typeof = "integer", length = 3, neg.values = FALSE, na.contain = FALSE)
-# No result displayed because the output list is assigned into res (see below the print argument)
-res <- fun_check(data = vec1, class = "integer")
-res
-# with NULL, the function systematically report a checking problem
-fun_check(data = NULL, class = "integer")
-
-### Argument class, typeof, mode and length are the same as the corresponding R function, except class which 1) has also "vector" and 2) remains "matrix" for matrices and not "matrix" "array"
-# Example
-fun_check(data = vec1, 
-    class = "vector", 
-    typeof = "integer", 
-    mode = "numeric", 
-    length = 5, 
-)
-# Warning: the function does not check for inconsistencies between arguments. It just checks if everything is ok between arguments values and data
-fun_check(data = vec1, 
-    typeof = "integer", 
-    mode = "character", # the mode "character" exists but is inconsistant with typeof "integer". However, this aspect is not signaled by the function
-)
-# Error message due to wrong value in the class and length arguments
-fun_check(data = vec1, 
-    mode = "integer", # the mode "integer" does not exist in the mode() function of R
-)
-
-### Argument prop
-fun_check(data = mat2, 
-    prop = TRUE # Check for values between 0 and 1 only
-)
-
-### Argument double.as.integer.allowed
-fun_check(data = vec3, typeof = "integer",
-    double.as.integer.allowed = TRUE # with TRUE, integers stored as double are accepted
-)
-
-### Argument options
-fun_check(data = vec4, 
-    options = c("pearson", "spearman", "kendall")
-)
-
-### Argument all.options.in.data
-# No error
-fun_check(data = vec5,
-    options = c("a", "b"), 
-    all.options.in.data = TRUE
-)
-# No error
-fun_check(data = vec5,
-    options = c("a", "b", "c"), 
-    all.options.in.data = FALSE
-)
-# Error
-fun_check(data = vec5,
-    options = c("a", "b", "c"), 
-    all.options.in.data = TRUE
-)
-
-### Argument na.contain
-fun_check(data = mat2, class = "matrix", prop = TRUE,
-    na.contain = FALSE # with TRUE, integers stored as double are accepted
-)
-
-### Argument neg.values
-# Warning: only considered if set to FALSE, to check for non negative values when class is set to "vector", "numeric", "matrix", "array", "data.frame", "table", or typeof is set to "double", "integer", or mode is set to "numeric"
-fun_check(data = mat1, class = "matrix",
-    neg.values = FALSE # with TRUE, integers stored as double are accepted
-)
-
-### Argument print
-# No error message printed because print is FALSE
-res <- fun_check(data = mat1, class = "data.frame",
-    print = FALSE
-)
-# Error message printed
-res <- fun_check(data = mat1, class = "data.frame",
-    print = TRUE
-)
-# Even if print is TRUE, no error message printed because no error
-res <- fun_check(data = mat1, class = "matrix",
-    print = TRUE
-)
-
-
-### Arguments data.name and fun.name
-# Example
-tempo <- fun_check(data = vec1, class = "integer", 
-    data.name = "OBSERVATION_1", 
-    fun.name = "FUNCTION_1"
-)
-tempo$text
-# In fact, these two arguments are interesting when fun_check() is used inside functions
-fun1 <- function(arg1){
-    tempo <- fun_check(data = arg1, class = "integer", 
-        data.name = NULL, # if NULL, the name displayed is arg1
-        fun.name = NULL # if NULL, no name displayed
-    )
-    if(tempo$problem == TRUE){
-        cat(paste0("\n\n================\n\n", tempo$text, "\n\n================\n\n"))
-    }
-}
-fun1(arg1 = vec4) # error message because arg1 requires a vector of integers
-
-
-
-### All the arguments
-# See the examples of fun_info() to test different classes of objects
-fun_check(
-    data = vec1, 
-    class = "integer", 
-    typeof = NULL, 
-    mode = NULL, 
-    length = NULL, 
-    prop = FALSE, 
-    double.as.integer.allowed = FALSE, 
-    options = NULL, 
-    all.options.in.data = FALSE, 
-    na.contain = FALSE, 
-    neg.values = TRUE, 
-    print = FALSE, 
-    data.name = NULL, 
-    fun.name = NULL
-)
-

examples_fun_info.R

-
-
-
-
-
-######## fun_info() #### recover object information
-
-### Datasets
-vec1 <- -1:3 # vector of integers
-vec2 <- 1:3 / 3 # vector of proportions
-vec3 <- c(1, 2, NA, -Inf) # vector of integers but stored as "double", with NA and Inf
-vec4 <- "pearson" # vector of characters
-vec5 <- c("a", "b","a", NA) # vector of characters with NA
-cpx <- as.complex(1) # complex
-mat1 <- matrix(vec1) # 1D matrix of integers
-mat2 <- matrix(c(1:5, NA), ncol = 2, dimnames = list(c("ROW1", "ROW2", "ROW3"), c("M1", "M2"))) # 2D matrix of floats with NA
-df1 <- as.data.frame(mat2) # data.frame
-l1 <- list(L1 = 1:3, L2 = letters[1:3]) # list
-fac1 <- factor(rep(letters[4:6], c(4:6))) # factor
-tab1 <- table(fac1) # 1D table
-tab2 <- table(fac1, fac1) # 2D table
-exp1 <- expression("a") # object of class "expression", mode "expression" & type "expression"
-name1 <- substitute(exp1) # object of class "name", mode "name" & type "symbol"
-fun1 <- mean # closure function of class "function", mode "function" & type "closure"
-fun2 <- sum # primitive function of class "function", mode "function" & type "builtin"
-fun3 <- get("<-") # primitive function of class "function", mode "function" &  type "special"
-env1 <- new.env() # environment
-s4 <- show # S4 object
-call1 <- call("call1") # object of class "call", mode "call" & type "language"
-
-### Datasets info
-vec1 # vector of integers
-vec2 # vector of proportions
-vec3 # vector of integers but stored as "double", with NA
-vec4 # vector of characters
-vec5 # vector of characters with NA
-mat1 # 1D matrix of integers
-mat2 # 2D matrix of floats with NA
-df1 # data.frame
-l1 # list
-fac1 # factor
-tab1 # 1D table
-tab2 # 2D table
-exp1 # object of class "expression", mode "expression" & type "expression"
-name1 # object of class "name", mode "name" & type "symbol"
-fun1 # closure function of class "function", mode "function" & type "closure"
-fun2 # primitive function of class "function", mode "function" & type "builtin"
-fun3 # primitive function of class "function", mode "function" &  type "special"
-env1 # environment
-s4 # S4 object
-call1 # object of class "call", mode "call" &  type "language"
-
-
-### Simple example
-fun_info(data = vec1) # vector of integers
-fun_info(data = vec2) # vector of proportions
-fun_info(data = vec3) # vector of integers but stored as "double", with NA and Inf
-fun_info(data = vec4) # vector of characters
-fun_info(data = vec5) # vector of characters with NA
-fun_info(data = mat1) # 1D matrix of integers
-fun_info(data = mat2) # 2D matrix of floats with NA
-fun_info(data = df1) # data.frame
-fun_info(data = l1) # list
-fun_info(data = fac1) # factor
-fun_info(data = tab1) # 1D table
-fun_info(data = tab2) # 2D table
-fun_info(data = exp1) # object of class "expression", mode "expression" & type "expression"
-fun_info(data = name1) # object of class "name", mode "name" & type "symbol"
-fun_info(data = fun1) # closure function of class "function", mode "function" & type "closure"
-fun_info(data = fun2) # primitive function of class "function", mode "function" & type "builtin"
-fun_info(data = fun3) # primitive function of class "function", mode "function" &  type "special"
-fun_info(data = env1) # environment
-fun_info(data = s4) # S4 object
-fun_info(data = call1) # object of class "call", mode "call" &  type "language"
-
-
-
-### All the arguments
-fun_info(
-    data = vec1, 
-    n = 1, # number of element to display per compartment of the output list (i.e., head(..., n))
-    warn.print = FALSE
-)
-
-
-
-