update documentation

NEWS.md

@@ -1,22 +1,63 @@
 
-# banffIT 1.0.0
+# banffIT 0.1.0
 
-This package is a xxx xxx xxx
+The banffIT package provides provides functions to assign standardized
+diagnosis 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
+[banff_launcher()](https://PersonalizedTransplantCare.github.io/banffIT-documentation/reference/banff_launcher.html)
+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), assign diagnoses, and create
+a summary report.
 
-## Helper functions
+## Main functionality
+
+- function `banff_launcher()` 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_diagnosis()](https://PersonalizedTransplantCare.github.io/banffIT-documentation/reference/add_diagnosis.html)
+  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.
+
+## additional functions (used in the main function, but can be used separately)
+
+- function `banff_dataset_evaluate()` This function takes a dataset and
+  evaluates its format and content based on the accepted format
+  specified in the data dictionary.
 
-- xxx xxx xxx
+- function `calculate_adequacy()` A tibble object with two columns: the
+  calculated adequacy (adequacy_calculated) and the adequacy specified
+  in input (adequacy_input).
 
-## functions xxx xxx xxx
+- function `dataset_cat_as_labels()`
+  [Function](https://maelstrom-research.github.io/madshapR-documentation/reference/dataset_cat_as_labels.html)
+  exported from the madshapR package.
+
+- function `add_diagnosis()` This function takes a dataset and returns a
+  diagnosis for each observation. For the function to run, the dataset
+  must not contain any errors that
+  [banff_launcher()](https://PersonalizedTransplantCare.github.io/banffIT-documentation/reference/banff_launcher.html)
+  would have detected. Please prefer using `banff_launcher()` to run
+  additional tests.
+
+- function `dataset_summarize()`
+  [Function](https://maelstrom-research.github.io/madshapR-documentation/reference/summarize.html)
+  exported from the madshapR package.
+
+## Helper functions
 
-These functions allows to xxx xxx xxx.
+- function `get_banff_dictionary()` This function gets the data
+  dictionary used to control the consistency of the banff dataset.
 
-- function `add_diagnosis()` does xxx xxx xxx
-- function `banff_dataset_evaluate()` does xxx xxx xxx
-- function `banff_dataset_summarize()` does xxx xxx xxx
-- function `banff_launcher()` does xxx xxx xxx
-- function `calculate_adequacy()` does xxx xxx xxx
-- function `dataset_cat_as_labels()` does xxx xxx xxx
-- function `get_banff_dictionary()` does xxx xxx xxx
-- function `is_banff_dataset()` does xxx xxx xxx
-- function `banffIT_website()` does xxx xxx xxx
+- function `banffIT_website()` This function sends the user to the
+  online documentation for the package, which includes a description of
+  the latest version of the package, vignettes, user guides, and a
+  reference list of functions and help pages.

R/00_utils.R

@@ -2,7 +2,7 @@
 #' Get the banff data dictionary
 #'
 #' @description
-#' This function gets the data dictionary used to control the consistancy of
+#' This function gets the data dictionary used to control the consistency of
 #' the banff dataset.
 #'
 #' @param which Indicates which banff dictionary to get. Either "input" or
@@ -136,7 +136,7 @@ The possible `language` are : ",toString(labels))
 #' @export
 banffIT_website <- function(){
 
-  browseURL("https://maelstrom-research.github.io/banffIT-documentation/")
+  browseURL("https://PersonalizedTransplantCare.github.io/banffIT-documentation/")
 
 }
 

R/02_algorithm.R

@@ -984,3 +984,72 @@ madshapR::dataset_cat_as_labels
 #' @keywords imported
 #' @export
 madshapR::dataset_summarize
+
+
+
+#  @title
+#  summarise a banff dataset with its diagnosis
+#
+#  @description
+#  Assesses and summarizes the content and structure of a banff dataset (with
+#  diagnosis) and generates reports of the results. This function can be used
+#  to evaluate data structure, and to summarize additional information about
+#  variable distributions and descriptive statistics.
+#
+#  @param banff_diagnosis A banff dataset object with diagnosis.
+#  @param banff_assessment A tibble object.
+#  @param banff_dict A list of tibble objects giving information on the
+#  assessment of the banff dataset.
+#  @param banff_file_name A character string specifying the name of the dataset.
+#
+#  @return
+#  A list of tibble objects giving information on the summary of the banff
+#  dataset.
+#
+#  @examples
+#  {
+#
+#  library(fabR)
+#  banff_file <- system.file("extdata", "example.xlsx", package = "banffIT")
+#  banff_dataset <- read_excel_allsheets(banff_file)[1,]
+#  banff_dataset_evaluate(banff_dataset)
+#
+#  }
+#
+#  @import dplyr tidyr madshapR
+#  @importFrom rlang .data
+#  @export
+# banff_dataset_summarize <- function(
+#     banff_diagnosis,
+#     banff_assessment = NULL,
+#     banff_dict,
+#     banff_file_name) {
+#
+#   if(is.null(banff_assessment))
+#     banff_assessment <- banff_dataset_evaluate(banff_diagnosis$codeset)
+#
+#   banff_report <-
+#     banff_dataset_summarize(
+#       dataset = banff_diagnosis$codeset,
+#       data_dict = banff_dict,
+#       dataset_name = banff_file_name)
+#
+#   banff_report$`Dataset assessment - input`     <- banff_assessment$`Dataset assessment`
+#   banff_report$`Dataset assessment - diagnosis` <- banff_report$`Dataset assessment`
+#   banff_report$`Dataset assessment`             <- NULL
+#   banff_report$`Variables summary (all)`        <- banff_assessment$`Data dictionary summary`
+#
+#   banff_report$`Dataset assessment - diagnosis` <-
+#     banff_report$`Dataset assessment - diagnosis` %>%
+#     select("column" = "name","condition" = "Quality assessment comment", "value") %>%
+#     dplyr::filter(!.data$`column` %in% banff_report$`Dataset assessment - input`$column)
+#
+#   banff_report <- banff_report[unique(c(
+#     "Overview","Dataset assessment - input",
+#     "Dataset assessment - diagnosis", names(banff_report)))]
+#
+#   return(banff_report)
+#
+# }
+
+

README.md

@@ -12,14 +12,16 @@ The banffIT package provides provides functions to assign standardized
 diagnosis 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 [banff_launcher()](banff_launcher()) 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), assign diagnoses, and create a summary report.
+main function
+[banff_launcher()](https://PersonalizedTransplantCare.github.io/banffIT-documentation/reference/banff_launcher.html)
+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), assign diagnoses, and create
+a summary report.
 
 # Get started
 
-## Install the package
+## Install the package and use the example file
 
 ``` r
 # To install madshapR:
@@ -28,4 +30,8 @@ install.packages('banffIT')
 library(banffIT)
 # If you need help with the package, please use:
 banffIT_website()
+
+# use the example file provided. remplace tempdir by a directory name.
+banff_file <- system.file("extdata", "example.xlsx", package = "banffIT")
+banff_launcher(banff_file, output_folder = tempdir())
 ```

vignettes/banffIT-vignette.Rmd

@@ -29,7 +29,7 @@ report.
 ## Install the package and use the example file
 
 ```{r, eval=FALSE}
-# To install madshapR:
+# To install banffIT:
 install.packages('banffIT')
 
 library(banffIT)