## ----include = FALSE---------------------------------------------------------- knitr::opts_chunk$set( collapse = TRUE, comment = "#>" ) ## ----eval=FALSE--------------------------------------------------------------- # # Load relevant packages # library(Rmonize) # library(tidyverse) # Collection of R packages for data science ## ----eval=FALSE--------------------------------------------------------------- # # Get the input datasets # dataset_study1 <- Rmonize_examples$input_dataset_study1 # dataset_study2 <- Rmonize_examples$input_dataset_study2 # dataset_study3 <- Rmonize_examples$input_dataset_study3 # dataset_study4 <- Rmonize_examples$input_dataset_study4 # dataset_study5 <- Rmonize_examples$input_dataset_study5 # # # Get the DataSchema # dataschema <- Rmonize_examples$DataSchema # # # Get the Data Processing Elements # dpe_with_errors <- Rmonize_examples$`Data_Processing_Element_with errors` # # This version contains some examples of potential processing errors. ## ----eval=FALSE--------------------------------------------------------------- # # Create an input dossier # input_dossier <- dossier_create(list( # dataset_study1, # dataset_study2, # dataset_study3, # dataset_study4, # dataset_study5)) # # # Run processing function # harmonized_dossier_with_errors <- harmo_process( # object = input_dossier, # dataschema = dataschema, # data_proc_elem = dpe_with_errors, # harmonized_col_dataset = 'adm_study_id') # Identifies the harmonized variable # # to use as dataset identifiers ## ----fig.cap="Subset of processing information printed in the console, including messages about errors in running individual algorithms.", out.width="80%", fig.align="center",echo=FALSE---- knitr::include_graphics("images/vig4_fig01.png") ## ----eval=FALSE--------------------------------------------------------------- # # To identify processing errors to correct in the DPE # show_harmo_error( # harmonized_dossier_with_errors, # show_warnings = TRUE) # Can be informative, but can also be turned off, e.g., # # if there are known warnings produced by processing algorithms ## ----fig.cap="Subset of output from show_harmo_error() printed in the console.", out.width="80%", fig.align="center",echo=FALSE---- knitr::include_graphics("images/vig4_fig02.png") ## ----fig.cap="Example of locating the errors in the DPE document.", out.width="80%", fig.align="center",echo=FALSE---- knitr::include_graphics("images/vig4_fig03.png") ## ----eval=FALSE--------------------------------------------------------------- # # Get corrected DPEs with changes made based on error messages # dpe_no_errors <- # Rmonize_examples$`Data_Processing_Element_no errors` %>% # as_data_proc_elem() # # # Run processing function # harmonized_dossier <- harmo_process( # object = input_dossier, # dataschema = dataschema, # data_proc_elem = dpe_no_errors, # harmonized_col_dataset = 'adm_study_id' # Identifies the harmonized variable # # to use as dataset identifiers # ) # # # Confirm there are no errors # show_harmo_error( # harmonized_dossier, # show_warnings = TRUE # ) ## ----eval=FALSE--------------------------------------------------------------- # # Save the harmonized dossier as R file # # WARNING: This script creates a folder 'tmp'. # output_path <- paste0('tmp/',basename(tempdir())) # dir.create(output_path) # saveRDS(harmonized_dossier, paste0(output_path,"/harmonized_dossier.rds"))