R/read_csv.R

In personalscience/cgmr: Continuous Glucose Monitor Data Analysis

# Initial constants ----

utils::globalVariables(c("glucose_scan",
                         "glucose_historic",
                         "strip_glucose",
                         "hist",
                         "notes",
                         "Device Timestamp",
                         "Record Type",
                         "Historic Glucose mg/dL",
                         "Scan Glucose mg/dL",
                         "Strip Glucose mg/dL",
                         "Notes",
                         "Device",
                         "Serial Number",
                         "Non-numeric Food",
                         "Carbohydrates (grams)",
                         "Time (UTC)",
                         "Type of Reading",
                         "Glucose Reading (mg/dL)",
                         "food",
                         "time",
                         "timestamp",
                         "user_id",
                         "date_ch"
                         ))

#' @title Possible values for `Activity` column in Notes.
NOTES_COLUMNS <- c("Start", "End", "Activity","Comment", "Z","user_id", "TZ")
ACTIVITY_TYPES <- c("Sleep", "Event", "Food","Exercise")


# Read CSV ----

#' @title name of the person associated with a Libreview glucose file.
#' @description
#' Given a valid Libreview file, return a string of the form first_name last_name
#' @param filepath path to the CSV file
#' @importFrom stringr str_split str_squish str_detect
#' @return a space-separated character string made of first_name last_name. NA if no name found
#' @export
name_from_libreview_file <- function(filepath) {
  first2 <- readLines(con=filepath,2)
  if (str_detect(first2[1], "Patient"))
  {name <- str_split(first2[2],pattern=",")[[1]][1]}
  else name <- str_split(first2[1],pattern=",")[[1]][5]
  return(str_squish(name))
}


#' Read a raw libreview CSV file and return it as a plain dataframe
#' @title Read a standard format Libreview CSV file
#' @return a canonical glucose value dataframe
#' @param file path to a valid Libreview CSV file
#' @export
#' @import readr magrittr tibble
#' @import lubridate stringr
libreview_csv_df <- function(file=system.file("extdata",
                                              package = "cgmr",
                                              "Firstname2Lastname2_glucose.csv")){

  firstline <- readLines(con = file, 1) %>%
    str_split(pattern = ",", simplify = TRUE)

  skip_lines <- if_else(firstline[1] == "Glucose Data", 1, 2)

  name <- name_from_libreview_file(file)

  glucose_raw <-
    readr::read_csv(file, skip = skip_lines, col_types = "cccdddddcddddcddddd") %>%
    transmute(
      timestamp = lubridate::mdy_hm(`Device Timestamp`),
      record_type = `Record Type`,
      glucose_historic = `Historic Glucose mg/dL`,
      glucose_scan = `Scan Glucose mg/dL`,
      strip_glucose = `Strip Glucose mg/dL`,
      notes = if_else(!is.na(Notes), paste0("Notes=",Notes),
                      Notes),
      device = `Device`,
      serial_number = `Serial Number`,
      food = `Non-numeric Food`,
      carbs = `Carbohydrates (grams)`,

    )

  return(list(glucose_raw = glucose_raw, name = name))

}

#' @title Convert a Libreview Dataframe to a Canonical Dataframe
#' @param libreview_raw dataframe of raw values as read from Libreview CSV file
#' @return dataframe in canonical format
#' @export
glucose_df_from_libreview_raw <- function(libreview_raw) {
  glucose_df <- libreview_raw %>%
    #dplyr::filter(record_type != 6) %>% # Record type 6 does nothing
    transmute(`time` = `timestamp`,
              scan = glucose_scan,
              hist = glucose_historic,
              strip = strip_glucose,
              value = hist,
              food = notes) # dplyr::if_else(is.na(notes),notes, paste0("Notes=",notes))) #dplyr::if_else(is.na(notes),"no", "yes"))#paste0("Notes=",notes)))


  return(glucose_df)
}


#' Read a valid libreview CSV file and return a dataframe and new user id
#' Since Libreview files don't already include a user ID, append one to the dataframe that is returned.
#' Importantly, datetimes are assumed to be `Sys.timezone()`.
#' @title Read a standard format Libreview CSV file
#' @return a canonical glucose value dataframe
#' @param file path to a valid Libreview CSV file
#' @param user_id new user ID to be appended to the dataframe
#' @export
#' @import readr magrittr tibble
#' @import lubridate stringr
glucose_df_from_libreview_csv <- function(file=system.file("extdata",
                                                           package = "cgmr",
                                                           "Firstname2Lastname2_glucose.csv"),
                                          user_id = 1234) {


  firstline <- readLines(con = file, 1) %>%
    str_split(pattern = ",", simplify = TRUE)

  skip_lines <- if_else(firstline[1] == "Glucose Data", 1, 2)

  glucose_raw <- libreview_csv_df(file)[["glucose_raw"]]

  glucose_df <- glucose_df_from_libreview_raw(glucose_raw)

  glucose_df %>% add_column(user_id = user_id)

}

#' @title Notes dataframe from a CSV
#' @description Return a canonical notes dataframe from a properly-constructed Notes CSV file.
#' @param file path to a valid notes CSV file
#' @param user_id user ID to associate with this dataframe
#' @return dataframe for a valid notes CSV file
#' @export
notes_df_from_csv <- function(file=system.file("extdata", package="cgmr", "FirstName1Lastname1_notes.csv"),
                              user_id = 1235) {


  notes <-   read_csv(file, show_col_types = FALSE) %>%
  transmute(Start = mdy_hm(.data[["Start"]]),
            End = mdy_hm(.data[["End"]]),
            Activity = factor(.data[["Activity"]], levels = ACTIVITY_TYPES),
            Comment =  .data[["Comment"]],
            Z = .data[["Z"]],
            user_id = user_id,
            TZ = as.integer(NA))


  return(notes)
}


#' @title Return all `glucose_records` that have something in the notes field
#' @description Notes are sometimes located in the "Notes" field of a CSV file,
#' which in turn will be saved in `glucose_records`.
#' Harvest any such notes and place them in `notes_records`.
#' @param glucose_records valid glucose record dataframe
#' @param user_id User ID
#' @return dataframe of
#' @export
#'
notes_df_from_glucose_table <- function(glucose_records,
                                        user_id = 1234) {


  ID = user_id

  food_records <- glucose_records %>%
    filter(user_id == ID) %>%
    filter(!is.na(`food`)) %>% collect() %>%
    transmute(Start = `time`,
              End = lubridate::as_datetime(NA),
              Activity = factor("Food", levels = ACTIVITY_TYPES),
              Comment = as.character(stringr::str_replace(`food`,"Notes=","")),
              Z = as.numeric(NA),
              user_id = user_id)

  return(food_records)

}