annotate_monitor: Single function to call when reading monitor files.

In odeleongt/pemr: Use Data From Personal Environmental Monitors

Description

Typical output from personal environmental monitors will be plain text files containing either raw data in a readily usable format (e.g. PATS+, UPAS) or raw data in binary format which needs to be pre-processed using the monitor software (e.g. ECM).

'annotate_monitor()' will read data from the header of a single file and return a data frame with all the metadata contained in that header.

Usage

annotate_monitor(file, type, ...)

Arguments

file	Path to the file containing monitor metadata.
type	Type of monitor with which the data was recorded. Currently there are two valid types: * "ecm" or "ecm-full": metadata from ECM. Any other option will be coerced to "unknown" and return an empty data frame.
...	Ignored

Details

Usually you will be interested in reading data form multiple files, this can be easily achieved by listing in a data frame all files and types you want to read and iterating over it with purrr::map2 as shown in the examples below. Use annotate_monitor in the same way to read in the header metadata for each file, and then use tidyr::unnest to extract all the metadata for each file.

Value

A data frame with all columns from the monitor file.

Examples

## Not run: 
# Load required packages
library(package = "pemr")

# Define files and types. This can be any data frame, so composing data in a
# spreadsheet and reading it in works too
data_frame(
 files_col = c("path/to/file1.csv", "path/to/file2.csv"),
 types_col = c("ecm", "upas")
) %>%
mutate(
  data = map2(files_col, types_col, read_monitor),
  header = map2(files_col, types_col, annotate_monitor)
) %>%
unnest()

## End(Not run)

odeleongt/pemr documentation built on May 3, 2019, 10:44 p.m.