corrections after CRAN first release submission

.Rbuildignore

@@ -11,3 +11,4 @@
 ^README.Rmd
 ^NEWS.Rmd
 ^cran-comments\.md$
+^CRAN-SUBMISSION$

DESCRIPTION

@@ -25,14 +25,17 @@ Authors@R:
              role=c("ctb"),
              email="twey@maelstrom-research.org"))
 Maintainer: Guillaume Fabre <guijoseph.fabre@gmail.com>
-Description: The goal of this package is to provide functions to assign 
-    standardized diagnoses using the Banff Classification (Category 1 to 6 
-    diagnoses, including Acute and Chronic active T-cell mediated rejection as 
-    well as Active, Chronic active, and Chronic antibody mediated rejection). 
-    The main function considers a minimal dataset containing biopsies 
-    information in a specific format (described by a data dictionary), verifies 
-    its content and format (based on the data dictionary), assigns diagnoses, 
-    and creates a summary report.
+Description: Assigns standardized diagnoses using the Banff Classification
+    (Category 1 to 6 diagnoses, including Acute and Chronic active T-cell
+    mediated rejection as well as Active, Chronic active, and Chronic antibody
+    mediated rejection). The main function considers a minimal dataset
+    containing biopsies information in a specific format (described by a data
+    dictionary), verifies its content and format (based on the data dictionary),
+    assigns diagnoses, and creates a summary report. The package is developed on
+    the reference guide to the Banff classification of renal allograft pathology
+    Roufosse C, Simmonds N, Clahsen-van Groningen M, et al. A (2018) <doi:10.1097/TP.0000000000002366>.
+    The full description of the Banff classification is available at
+    <https://banfffoundation.org/central-repository-for-banff-2019-resources-3/>.
 License: GPL-3
 Depends: R (>= 3.4)
 URL: https://github.com/PersonalizedTransplantCare/banffIT

NEWS.md

@@ -20,9 +20,9 @@ dictionary), assigns diagnoses, and creates a summary report.
   diagnosis for each observation (using the function `add_diagnoses()`
   internally). The output dataset, along with its associated labels
   (“label:en” by default) are provided to the user in an Excel format
-  file accessible in the output_folder specified (the working directory
-  by default). The output dataset comes with a report that summarizes
-  information about variable distributions and descriptive statistics.
+  file accessible in the output_folder specified. The output dataset
+  comes with a report that summarizes information about variable
+  distributions and descriptive statistics.
 
 ## Additional functions (used in the main function, but can be used separately)
 

R/02_banff_launcher.R

@@ -2,16 +2,16 @@
 #' Launch the program
 #'
 #' @description
-#' This function takes a path string identifying the input file path. The function
-#' internally runs a series of tests that assess the input dataset. If any
-#' of these tests fails, the user gets information allowing them to correct the
-#' input dataset and rerun the process. Once all tests pass, the dataset
+#' This function takes a path string identifying the input file path. The
+#' function internally runs a series of tests that assess the input dataset. If
+#' any of these tests fails, the user gets information allowing them to correct
+#' the input dataset and rerun the process. Once all tests pass, the dataset
 #' is given as an output with a diagnosis for each observation (using the
 #' function [add_diagnoses()] internally). The output dataset, along with its
 #' associated labels (`label:en` by default) are provided to the user in an Excel
-#' format file accessible in the output_folder specified (the working directory by
-#' default). The output dataset comes with a report that summarizes information
-#' about variable distributions and descriptive statistics.
+#' format file accessible in the output_folder specified. The output dataset
+#' comes with a report that summarizes information about variable distributions
+#' and descriptive statistics.
 #'
 #' @param input_file A character string identifying the path of the input file
 #' (must be a CSV or a one sheet Excel file)
@@ -48,7 +48,7 @@
 #' @export
 banff_launcher <- function(
     input_file,
-    output_folder = getwd(),
+    output_folder,
     language = "label:en",
     option_filter,
     detail = FALSE){
@@ -92,7 +92,7 @@ Press [enter] to continue or [esc] to quit.
 
   # check the folder (to be created if does not exists).
   if(path_ext(output_folder) != "")
-    stop(call. = FALSE,"Please specify a valid directory name.")
+    stop(call. = FALSE,"Please specify a valid directory name (in quote).")
   if(!dir.exists(output_folder)) dir_create(output_folder)
 
   # names of objects to be generated in the folder. construct name and check previous existence.

README.md

@@ -62,7 +62,7 @@ banffIT_website()
 input_file = system.file("extdata", "example.xlsx", package = "banffIT")
 banff_launcher(
   input_file = input_file,
-  output_folder = 'folder_path/example',
+  output_folder = tempdir(), # 'folder_path/example'
   language = 'label:en',
   option_filter = adequacy == 1,
   detail = TRUE)

cran-comments.md

@@ -3,3 +3,16 @@
 0 errors | 0 warnings | 1 note
 
 * This is a new release.
+
+### CRAN comments after first attempt of release 
+
+> Thanks, we see:
+The Description field contains
+https:https://banfffoundation ...
+the "https:" part is doubled.
+Please fix and resubmit.
+
+<https:https://banfffoundation.org/central-repository-for-banff-2019-resources-3/>.
+
+Done, Thanks for noticing it !
+

vignettes/banffIT-vignette.Rmd

@@ -14,17 +14,17 @@ knitr::opts_chunk$set(
 )
 ```
 
-This package is designed to assign standardized diagnoses using the 
-Banff Classification (Category 1 to 6 diagnoses, including Acute and Chronic 
-active T-cell mediated rejection as well as Active, Chronic active, and Chronic 
-antibody mediated rejection). 
+This package is designed to assign standardized diagnoses using the
+Banff Classification (Category 1 to 6 diagnoses, including Acute and Chronic
+active T-cell mediated rejection as well as Active, Chronic active, and Chronic
+antibody mediated rejection).
 
-The following steps will guide you in this process of diagnosis assignment with 
-the package. To get your dataset ready and in a correct format, you must 
+The following steps will guide you in this process of diagnosis assignment with
+the package. To get your dataset ready and in a correct format, you must
 refer to the data dictionary provided with the package
 <a href="https://PersonalizedTransplantCare.github.io/banffIT-documentation/templates/banff_dictionary.xlsx">here</a>
-(or using the function `get_banff_dictionary()` in R). This data dictionary 
-contains metadata specifying how your input dataset should be formatted and what 
+(or using the function `get_banff_dictionary()` in R). This data dictionary
+contains metadata specifying how your input dataset should be formatted and what
 information it must contain.
 
 # 1. Having your dataset ready
@@ -33,33 +33,33 @@ A template (available
 <a href="https://PersonalizedTransplantCare.github.io/banffIT-documentation/templates/banff_template.xlsx" download class="external-link">here</a>
 or `get_banff_template()` in R) as well as an example dataset (available
 <a href="https://PersonalizedTransplantCare.github.io/banffIT-documentation/templates/banff_example.xlsx" download class="external-link">here</a>
-or `get_banff_example()` in R) are also available with the package to help you 
+or `get_banff_example()` in R) are also available with the package to help you
 construct and prepare your dataset.
 
 # 2. Run the process with the main function 
 
 The main function `banff_launcher()` will go through 3 steps. It will:
 
-a) Evaluate your input dataset (using `banff_dataset_evaluate()` internally). 
-If your input dataset is not in the correct format or is missing information, 
-a report will be saved in your output folder and will flag variables and 
-rows that are not formatted properly. The next step will not run if the input 
+a) Evaluate your input dataset (using `banff_dataset_evaluate()` internally).
+If your input dataset is not in the correct format or is missing information,
+a report will be saved in your output folder and will flag variables and
+rows that are not formatted properly. The next step will not run if the input
 dataset is not in the correct format.
 
-b) Assign diagnosis to each observation (using `calculate_adequacy()` and 
+b) Assign diagnosis to each observation (using `calculate_adequacy()` and
 `add_diagnoses()` internally).
 
-c) Save the output dataset containing diagnoses,a summary report with 
+c) Save the output dataset containing diagnoses,a summary report with
 descriptive statistics of your output dataset, and the data dictionary.
 
 
 # 3. Use the example file
 
-This command example runs the diagnosis assignment process on the dataset 
+This command example runs the diagnosis assignment process on the dataset
 specified in the input_file path. The output files will be saved in
-path_folder/example. The diagnoses will be displayed in English and only 
-observation with adequacy == 1 will be taken into consideration due to the 
-option_filter argument. Finally, the output dataset will contain variables 
+path_folder/example. The diagnoses will be displayed in English and only
+observation with adequacy == 1 will be taken into consideration due to the
+option_filter argument. Finally, the output dataset will contain variables
 generated in the process due to the argument "detail" set to TRUE.
 
 ```{r, eval=FALSE}
@@ -75,7 +75,7 @@ banffIT_website()
 input_file = system.file("extdata", "example.xlsx", package = "banffIT")
 banff_launcher(
  input_file = input_file,
- output_folder = 'folder_path/example',
+ output_folder = tempdir(), # 'folder_path/example'
  language = 'label:en',
  option_filter = adequacy == 1,
  detail = TRUE)