documentation

R/iidda.analysis/R/pipeline_dependencies.R

@@ -13,7 +13,7 @@
 #' @export
 browse_pipeline_dependencies = function(dataset_ids
     , dependency_types = c("IsCompiledBy", "IsDerivedFrom", "References")
-    , metadata = iidda.api::ops$metadata(dataset_ids = dataset_ids)
+    , metadata = iidda.api::ops_staging$metadata(dataset_ids = dataset_ids)
   ) {
   dataset_ids = unique(dataset_ids)
   if (length(dataset_ids) > 1L) {

R/iidda.analysis/R/plot_prep.R

@@ -566,7 +566,24 @@ ComputeMovingAverage <- function(ma_window_length=52){
   }
 }
 
-
+#' Period Aggregator
+#'
+#' Create function that aggregates information over time periods, normalizes
+#' a count variable, and creates new fields to summarize this information.
+#'
+#' @param time_variable Name of the variable to characterize the temporal
+#' location of the time period.
+#' @param period_width_variable Name of variable to characterize the width
+#' of the time period.
+#' @param count_variable Name of variable to characterize the count variable
+#' being normalized.
+#' @param norm_variable Name of variable to be used to normalize the count
+#' variable.
+#' @param rate_variable Name of variable to be used to store the normalized
+#' count variable.
+#' @param norm_exponent Exponent to use in normalization. The default is `5`,
+#' which means `per 100,000`.
+#'
 #' @export
 PeriodAggregator = function(
     time_variable = "period_mid_time"
@@ -594,6 +611,12 @@ PeriodAggregator = function(
   }
 }
 
+#' Time Scale Picker
+#'
+#' @param time_scale_variable Variable identifying the time scale of records.
+#' The values of such a variable should be things like `"wk"`, `"mn"`, `"yr"`.
+#' @param time_group_variable Variable identifying a grouping variable for
+#' the time scales (e.g. a column identifying the year.).
 #' @export
 TimeScalePicker = function(
     time_scale_variable = "time_scale"

R/iidda.analysis/R/regex_query_tools.R

@@ -1,12 +1,12 @@
 #' Get field names for iidda queries
 #'
-#' @param response_type Character, one of `metadata`, `columns`, or 
+#' @param response_type Character, one of `metadata`, `columns`, or
 #'     `data_dictionary`
 #' @param data_type Character, one of `cdi`, `CDI`, or `Communicable Disease
 #'   Incidence` for disease incidence time series datasets, or `pop`, `Pop`,  or
 #'   `Population` for historical demographic census datasets"
 #'
-#' @return A Vector of field names, or if `response_type = "data_dictionary"`, a 
+#' @return A Vector of field names, or if `response_type = "data_dictionary"`, a
 #'    named list
 #'
 #' @importFrom stats na.omit
@@ -52,7 +52,7 @@ query_options <- function(response_type = c("metadata"
   if(!(data_type %in% c("Communicable Disease Incidence", "Population"))){
     stop(message = "`datatype` must be one of `cdi`, `CDI`, or `Communicable Disease Incidence` for disease incidence time series datasets, or `pop`, `Pop`,  or `Population` for historical demographic census datasets")}
   # query metadata
-  met <- iidda.api::ops$metadata(
+  met <- iidda.api::ops_staging$metadata(
     response_type = response_type
     , metadata_search = data_type
     , key = ".types .resourceType"
@@ -78,7 +78,7 @@ query_options <- function(response_type = c("metadata"
 #' @param entries List returned by \code{iidda.api::ops$metadata}
 #' @param metadata_search Character, field from which unique tokens are desired
 #'
-#' @return Character vector of unique tokens for a given field from all iidda 
+#' @return Character vector of unique tokens for a given field from all iidda
 #'    datasets
 
 unique_entries <- function(entries, metadata_search){
@@ -120,7 +120,7 @@ unique_field_entries <- function(response_type = c("metadata"
                                  , string_comparison = "contains"
                                  , sort = TRUE
 ){
-  entries <- iidda.api::ops$metadata(response_type = response_type
+  entries <- iidda.api::ops_staging$metadata(response_type = response_type
                                      , metadata_search = metadata_search
                                      , string_comparison = string_comparison)
   ue <- unique_entries(entries, metadata_search = metadata_search)