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#-------------------------------------------------------------------------------
# Copyright (c) 2019 OBiBa. All rights reserved.
#
# This program and the accompanying materials
# are made available under the terms of the GNU Public License v3.0.
#
# You should have received a copy of the GNU General Public License
# along with this program. If not, see <http://www.gnu.org/licenses/>.
#-------------------------------------------------------------------------------
#' Get the study data collection events (DCEs). Note that the DCEs are not fetched directly, they are extracted from study search results.
#'
#' @title Get the study data collection events
#' @family studies functions
#' @param mica A Mica object
#' @param query The search query
#' @param select The fields to be extracted
#' @param sort The fields to sort by
#' @param from From item
#' @param limit Max number of items. Note that this limit applies to the studies that are fetched, the resulting count of DCEs will be higher.
#' @param locale The language for labels (default is "en")
#' @param df Return a data.frame (default is TRUE)
#' @examples
#' \dontrun{
#' m <- mica.login("https://mica-demo.obiba.org")
#' mica.study.dces(m, query="study(in(Mica_study.methods-design,cohort_study))")
#' mica.logout(m)
#' }
#' @export
mica.study.dces <- function(mica, query="study()",
select=list("populations.dataCollectionEvents"),
sort=list("id"),
from=0, limit=100, locale="en", df=TRUE) {
q <- .append.rql(query, "study", select, sort, from, limit, locale)
res <- .post(mica, "studies", "_rql", query=list(query=q))
if (!df) {
return(res)
}
.reportListMetrics(res)
summaries <- res[["studyResultDto"]][["obiba.mica.StudyResultDto.result"]][["summaries"]]
if (length(summaries)>0) {
# get the count of DCEs
dcesCount <- 0
for (s in summaries) {
if (!is.null(s$populationSummaries)) {
for (pop in s$populationSummaries) {
dcesCount <- dcesCount + length(pop$dataCollectionEventSummaries)
}
}
}
id <- rep(NA, dcesCount)
name <- rep(NA, dcesCount)
description <- rep(NA, dcesCount)
studyId <- rep(NA, dcesCount)
populationId <- rep(NA, dcesCount)
start <- rep(NA, dcesCount)
end <- rep(NA, dcesCount)
model <- list()
idx <- 0
for(i in 1:length(summaries)) {
s <- summaries[[i]]
if (!is.null(s$populationSummaries)) {
for (pop in s$populationSummaries) {
if (!is.null(pop$dataCollectionEventSummaries)) {
for (dce in pop$dataCollectionEventSummaries) {
idx <- idx + 1
id[idx] <- paste0(s[["id"]], ":", pop[["id"]], ":", dce[["id"]])
name[idx] <- .extractLabel(locale, dce[["name"]])
description[idx] <- .extractLabel(locale, dce[["description"]])
studyId[[idx]] <- s[["id"]]
populationId[[idx]] <- paste0(s[["id"]], ":", pop[["id"]])
start[[idx]] <- .nullToNA(dce[["start"]])
end[[idx]] <- .nullToNA(dce[["end"]])
if (!is.null(dce[["content"]])) {
ct <- .flatten(jsonlite::fromJSON(dce[["content"]], simplifyDataFrame = FALSE), locale)
for (key in names(ct)) {
if (!(key %in% names(model))) {
d <- list()
d[[key]] <- rep(NA, dcesCount)
model <- append(model, d)
}
model[[key]][idx] <- ct[[key]]
}
}
}
}
}
}
}
df <- data.frame(id, name, description, studyId, populationId, start, end)
if (all(is.na(df$name))) {
df$name <- NULL
}
for (col in names(model)) {
if (!all(is.na(model[[col]]))) {
df[[col]] <- model[[col]]
}
}
df
} else {
data.frame()
}
}
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