# client for archive.opensensemap.org # in this archive, CSV files for measurements of each sensor per day is provided. #' Returns the default endpoint for the archive *download* #' While the front end domain is archive.opensensemap.org, file downloads #' are provided via sciebo. osem_archive_endpoint = function () { 'https://uni-muenster.sciebo.de/index.php/s/HyTbguBP4EkqBcp/download?path=/data' } #' Fetch day-wise measurements for a single box from the openSenseMap archive. #' #' This function is significantly faster than \code{\link{osem_measurements}} for large #' time-frames, as daily CSV dumps for each sensor from #' \href{https://archive.opensensemap.org}{archive.opensensemap.org} are used. #' Note that the latest data available is from the previous day. #' #' By default, data for all sensors of a box is fetched, but you can select a #' subset with a \code{\link[dplyr]{dplyr}}-style NSE filter expression. #' #' The function will warn when no data is available in the selected period, #' but continue the remaining download. #' #' @param x A `sensebox data.frame` of a single box, as retrieved via \code{\link{osem_box}}, #' to download measurements for. #' @param ... see parameters below #' @param fromDate Start date for measurement download, must be convertable via `as.Date`. #' @param toDate End date for measurement download (inclusive). #' @param sensorFilter A NSE formula matching to \code{x$sensors}, selecting a subset of sensors. #' @param progress Whether to print download progress information, defaults to \code{TRUE}. #' @return A \code{tbl_df} containing observations of all selected sensors for each time stamp. #' #' @seealso \href{https://archive.opensensemap.org}{openSenseMap archive} #' @seealso \code{\link{osem_measurements}} #' @seealso \code{\link{osem_box}} #' #' @export osem_measurements_archive = function (x, ...) UseMethod('osem_measurements_archive') #' @export osem_measurements_archive.default = function (x, ...) { # NOTE: to implement for a different class: # in order to call `archive_fetch_measurements()`, `box` must be a dataframe # with a single row and the columns `X_id` and `name` stop(paste('not implemented for class', toString(class(x)))) } # ============================================================================== # #' @describeIn osem_measurements_archive Get daywise measurements for one or more sensors of a single box. #' @export #' @examples #' \donttest{ #' # fetch measurements for a single day #' box = osem_box('593bcd656ccf3b0011791f5a') #' m = osem_measurements_archive(box, as.POSIXlt('2018-09-13')) #' #' # fetch measurements for a date range and selected sensors #' sensors = ~ phenomenon %in% c('Temperatur', 'Beleuchtungsstärke') #' m = osem_measurements_archive( #' box, #' as.POSIXlt('2018-09-01'), as.POSIXlt('2018-09-30'), #' sensorFilter = sensors #' ) #' } osem_measurements_archive.sensebox = function (x, fromDate, toDate = fromDate, sensorFilter = ~ T, ..., progress = T) { if (nrow(x) != 1) stop('this function only works for exactly one senseBox!') # filter sensors using NSE, for example: `~ phenomenon == 'Temperatur'` sensors = x$sensors[[1]] %>% dplyr::filter(lazyeval::f_eval(sensorFilter, .)) # fetch each sensor separately dfs = by(sensors, 1:nrow(sensors), function (sensor) { df = archive_fetch_measurements(x, sensor$id, fromDate, toDate, progress) %>% dplyr::select(createdAt, value) %>% #dplyr::mutate(unit = sensor$unit, sensor = sensor$sensor) %>% # inject sensor metadata dplyr::rename_at(., 'value', function(v) sensor$phenomenon) }) # merge all data.frames by timestamp dfs %>% purrr::reduce(dplyr::full_join, 'createdAt') } #' fetch measurements from archive from a single box, and a single sensor #' #' @param box A sensebox data.frame with a single box #' @param sensorId Character specifying the sensor #' @param fromDate Start date for measurement download, must be convertable via `as.Date`. #' @param toDate End date for measurement download (inclusive). #' @param progress whether to print progress #' @return A \code{tbl_df} containing observations of all selected sensors for each time stamp. archive_fetch_measurements = function (box, sensorId, fromDate, toDate, progress) { dates = list() from = fromDate while (from <= toDate) { dates = append(dates, list(from)) from = from + as.difftime(1, units = 'days') } http_handle = httr::handle(osem_archive_endpoint()) # reuse the http connection for speed! progress = if (progress && !is_non_interactive()) httr::progress() else NULL measurements = lapply(dates, function(date) { url = build_archive_url(date, box, sensorId) res = httr::GET(url, progress, handle = http_handle) if (httr::http_error(res)) { warning(paste( httr::status_code(res), 'on day', format.Date(date, '%F'), 'for sensor', sensorId )) if (httr::status_code(res) == 404) return(data.frame(createdAt = as.POSIXlt(x = integer(0), origin = date), value = double())) } measurements = httr::content(res, type = 'text', encoding = 'UTF-8') %>% parse_measurement_csv }) measurements %>% dplyr::bind_rows() } #' returns URL to fetch measurements from a sensor for a specific date, #' based on `osem_archive_endpoint()` #' @noRd build_archive_url = function (date, box, sensorId) { d = format.Date(date, '%F') format = 'csv' paste( osem_archive_endpoint(), d, osem_box_to_archivename(box), paste(paste(sensorId, d, sep = '-'), format, sep = '.'), sep = '/' ) } #' replace chars in box name according to archive script: #' https://github.com/sensebox/osem-archiver/blob/612e14b/helpers.sh#L66 #' #' @param box A sensebox data.frame #' @return character with archive identifier for each box osem_box_to_archivename = function (box) { name = gsub('[^A-Za-z0-9._-]', '_', box$name) paste(box$X_id, name, sep = '-') }