192 lines
11 KiB
R
192 lines
11 KiB
R
source("renv/activate.R")
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library(yaml)
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library(dplyr)
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library(readr)
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# we use reticulate but only load it if we are going to use it to minimize the case when old RAPIDS deployments need to update ther renv
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validate_deviceid_platforms <- function(device_ids, platforms, participant){
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if(length(device_ids) > 1 && length(platforms) == 1){
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if(platforms != "android" && platforms != "ios" && platforms != "infer")
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stop(paste0("If you have more than 1 device_id, platform should be 'android', 'ios' OR 'infer' but you typed: '", paste0(platforms, collapse = "s,"), "'. Participant file: ", participant))
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} else if(length(device_ids) > 1 && length(platforms) > 1){
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if(length(device_ids) != length(platforms))
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stop(paste0("The number of device_ids should match the number of platforms. Participant file:", participant))
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if(all(intersect(c("android", "ios"), unique(platforms)) != c("android", "ios")))
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stop(paste0("If you have more than 1 device_id and more than 1 platform, the platforms should be a mix of 'android' AND 'ios' but you typed: '", paste0(platforms, collapse = ","), "'. Participant file: ", participant))
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}
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}
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validate_inferred_os <- function(stream_container, participant_file, device, device_os){
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if(!is.na(device_os) && device_os != "android" && device_os != "ios")
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stop(paste0("We tried to infer the OS for ", device, " but 'infer_device_os' function inside '",stream_container,"' returned '",device_os,"' instead of 'android' or 'ios'. You can assign the OS manually in the participant file or report this bug on GitHub.\nParticipant file ", participant_file))
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}
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mutate_data <- function(scripts, data, data_configuration){
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for(script in scripts){
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if(grepl("\\.(R)$", script)){
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myEnv <- new.env()
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source(script, local=myEnv)
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attach(myEnv, name="sourced_scripts_rapids")
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if(exists("main", myEnv)){
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message(paste("Applying mutation script", script))
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data <- main(data, data_configuration)
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} else{
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stop(paste0("The following mutation script does not have main function: ", script))
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}
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# rm(list = ls(envir = myEnv), envir = myEnv, inherits = FALSE)
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detach("sourced_scripts_rapids")
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} else{ # python
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library(reticulate)
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module <- gsub(pattern = "\\.py$", "", basename(script))
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script_functions <- import_from_path(module, path = dirname(script))
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if(py_has_attr(script_functions, "main")){
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message(paste("Applying mutation script", script))
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data <- script_functions$main(data, data_configuration)
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} else{
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stop(paste0("The following mutation script does not have a main function: ", script))
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}
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}
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}
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return(data)
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}
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rename_columns <- function(name_maps, data){
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for(name in names(name_maps))
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data <- data %>% rename(!!tolower(name) := name_maps[[name]])
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return(data)
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}
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validate_expected_columns_mapping <- function(schema, rapids_schema, sensor, rapids_schema_file, stream_format){
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rapids_columns <- rapids_schema[[sensor]]
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if(is.null(rapids_columns))
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stop(paste(sensor, " columns are not listed in RAPIDS' column specification. If you are adding support for a new phone sensor, add any mandatory columns in ", rapids_schema_file))
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if("ANDROID" %in% schema[[sensor]]){
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android_columns <- names(schema[[sensor]][["ANDROID"]][["RAPIDS_COLUMN_MAPPINGS"]])
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if(length(setdiff(rapids_columns, android_columns)) > 0)
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stop(paste(sensor," mappings are missing one or more mandatory columns for ANDROID. The missing column mappings are for ", paste(setdiff(rapids_columns, android_columns), collapse=","),"in", stream_format, " (the mappings are case sensitive)"))
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if(length(setdiff(android_columns, rapids_columns)) > 0)
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stop(paste(sensor," mappings have one or more columns than required for ANDROID. The extra column mappings are for ", paste(setdiff(android_columns, rapids_columns), collapse=","),"in", stream_format, " (the mappings are case sensitive)"))
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}
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if("IOS" %in% schema[[sensor]]){
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ios_columns <- names(schema[[sensor]][["IOS"]][["RAPIDS_COLUMN_MAPPINGS"]])
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if(length(setdiff(rapids_columns, ios_columns)) > 0)
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stop(paste(sensor," mappings are missing one or more mandatory columns for IOS. The missing column mappings are for ", paste(setdiff(rapids_columns, ios_columns), collapse=","),"in", stream_format, " (the mappings are case sensitive)"))
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if(length(setdiff(ios_columns, rapids_columns)) > 0)
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stop(paste(sensor," mappings have one or more columns than required for IOS. The extra column mappings are for ", paste(setdiff(ios_columns, rapids_columns), collapse=","),"in", stream_format, " (the mappings are case sensitive)"))
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}
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}
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load_container_script <- function(stream_container){
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language <- if_else(endsWith(tolower(stream_container), "py"), "python", "r")
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if(language == "python"){
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library(reticulate)
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container <- import_from_path(gsub(pattern = "\\.py$", "", basename(stream_container)), path = dirname(stream_container))
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if(!py_has_attr(container, "pull_data"))
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stop(paste0("The following container.py script does not have a pull_data function: ", stream_container))
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if(!py_has_attr(container, "infer_device_os"))
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stop(paste0("The following container.py script does not have a infer_device_os function: ", stream_container))
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return(list("infer_device_os" = container$infer_device_os, "pull_data" = container$pull_data))
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} else if(language == "r"){
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source(stream_container)
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if(!exists("pull_data"))
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stop(paste0("The following container.R script does not have a pull_data function: ", stream_container))
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if(!exists("infer_device_os"))
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stop(paste0("The following container.R script does not have a infer_device_os function: ", stream_container))
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return(list("infer_device_os" = infer_device_os, "pull_data" = pull_data))
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}
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}
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get_devices_ids <- function(participant_data){
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devices_ids = c()
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for(device in participant_data)
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for(attribute in names(device))
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if(attribute == "DEVICE_IDS")
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devices_ids <- c(devices_ids, device[[attribute]])
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return(devices_ids)
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}
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validate_participant_file_without_device_ids <- function(participant_file){
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participant_data <- yaml::read_yaml(participant_file)
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participant_devices <- get_devices_ids(participant_data)
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if(length(participant_devices) == 0)
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stop("There are no device ids in this participant file for smartphones or wearables: ", participant_file)
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}
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pull_phone_data <- function(){
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participant_file <- snakemake@input[["participant_file"]]
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stream_format <- snakemake@input[["stream_format"]]
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rapids_schema_file <- snakemake@input[["rapids_schema_file"]]
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stream_container <- snakemake@input[["stream_container"]]
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data_configuration <- snakemake@params[["data_configuration"]]
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tables <- snakemake@params[["tables"]]
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sensor <- toupper(snakemake@params[["sensor"]])
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device_type <- "phone"
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output_data_file <- snakemake@output[[1]]
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validate_participant_file_without_device_ids(participant_file)
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participant_data <- read_yaml(participant_file)
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stream_schema <- read_yaml(stream_format)
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rapids_schema <- read_yaml(rapids_schema_file)
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devices <- participant_data$PHONE$DEVICE_IDS
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device_oss <- participant_data$PHONE$PLATFORMS
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device_oss <- replace(device_oss, device_oss == "multiple", "infer") # support multiple for retro compatibility
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validate_deviceid_platforms(devices, device_oss, participant_file)
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if(length(device_oss) == 1)
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device_oss <- rep(device_oss, length(devices))
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validate_expected_columns_mapping(stream_schema, rapids_schema, sensor, rapids_schema_file, stream_format)
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# ANDROID or IOS RAPIDS_COLUMN_MAPPINGS are guaranteed to be the same at this point (see validate_expected_columns_mapping function)
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expected_columns <- tolower(rapids_schema[[sensor]])
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participant_data <- setNames(data.frame(matrix(ncol = length(expected_columns), nrow = 0)), expected_columns)
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if(length(devices) == 0){
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warning("There were no PHONE device ids in this participant file:", participant_file)
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write_csv(participant_data, output_data_file)
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return()
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}
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container_functions <- load_container_script(stream_container)
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infer_device_os_container <- container_functions$infer_device_os
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pull_data_container <- container_functions$pull_data
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for(idx in seq_along(devices)){
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device <- devices[idx]
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message(paste0("\nProcessing ", sensor, " for ", device))
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device_os <- ifelse(device_oss[idx] == "infer", infer_device_os_container(data_configuration, device), device_oss[idx])
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validate_inferred_os(basename(stream_container), participant_file, device, device_os)
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if(!toupper(device_os) %in% names(stream_schema[[sensor]])){ # the current sensor is only available in a single OS (like PHONE_MESSAGES)
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warning(sensor, " data is not available for ", device_os, ". No data to download for ", device)
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next
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}
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os_table <- ifelse(length(tables) > 1, tables[[toupper(device_os)]], tables) # some sensor tables have a different name for android and ios
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columns_to_download <- c(stream_schema[[sensor]][[toupper(device_os)]][["RAPIDS_COLUMN_MAPPINGS"]], stream_schema[[sensor]][[toupper(device_os)]][["MUTATION"]][["COLUMN_MAPPINGS"]])
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columns_to_download <- columns_to_download[(columns_to_download != "FLAG_TO_MUTATE")]
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data <- pull_data_container(data_configuration, device, sensor, os_table, columns_to_download)
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if(!setequal(columns_to_download, colnames(data)))
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stop(paste0("The pulled data for ", device, " does not have the expected columns (including [RAPIDS_COLUMN_MAPPINGS] and [MUTATE][COLUMN_MAPPINGS]). The container script returned [", paste(colnames(data), collapse=","),"] but the format mappings expected [",paste(columns_to_download, collapse=","), "]. The conainer script is: ", stream_container))
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renamed_data <- rename_columns(columns_to_download, data)
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mutation_scripts <- stream_schema[[sensor]][[toupper(device_os)]][["MUTATION"]][["SCRIPTS"]]
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mutated_data <- mutate_data(mutation_scripts, renamed_data, data_configuration)
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if(!setequal(expected_columns, colnames(mutated_data)))
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stop(paste0("The mutated data for ", device, " does not have the columns RAPIDS expects. The mutation script returned [", paste(colnames(mutated_data), collapse=","),"] but RAPIDS expected [",paste(expected_columns, collapse=","), "]. One ore more mutation scripts in [", sensor,"][MUTATION][SCRIPTS] are adding extra columns or removing or not adding the ones expected"))
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participant_data <- rbind(participant_data, mutated_data %>% distinct())
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}
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participant_data <- participant_data %>% arrange(timestamp)
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write_csv(participant_data, output_data_file)
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}
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pull_phone_data() |