util_evaluate_calls: Generate a full DQ report, v2
In dataquieR: Data Quality in Epidemiological Research

util_evaluate_calls

R Documentation

Generate a full DQ report, v2

Description

Generate a full DQ report, v2

Usage

util_evaluate_calls(
  all_calls,
  study_data,
  meta_data,
  label_col,
  meta_data_segment,
  meta_data_dataframe,
  meta_data_cross_item,
  resp_vars,
  filter_result_slots,
  cores,
  debug_parallel,
  mode = c("default", "futures", "queue", "parallel"),
  mode_args
)

Arguments

`all_calls`	list a list of calls
`study_data`	data.frame the data frame that contains the measurements
`meta_data`	data.frame the data frame that contains metadata attributes of study data
`label_col`	variable attribute the name of the column in the metadata with labels of variables
`meta_data_segment`	data.frame – optional: Segment level metadata
`meta_data_dataframe`	data.frame – optional: Data frame level metadata
`meta_data_cross_item`	data.frame – optional: cross-item level metadata
`resp_vars`	variable list the name of the measurement variables for the report.
`filter_result_slots`	character regular expressions, only if an indicator function's result's name matches one of these, it'll be used for the report. If of length zero, no filtering is performed.
`cores`	integer number of cpu cores to use or a named list with arguments for parallelMap::parallelStart or NULL, if parallel has already been started by the caller. Can also be a cluster.
`debug_parallel`	logical print blocks currently evaluated in parallel
`mode`	character work mode for parallel execution. default is "default", the values mean: - default: use `queue` except `cores` has been set explicitly - futures: use the `future` package - queue: use a queue as described in the examples from the `callr` package by Csárdi and Chang and start sub-processes as workers that evaluate the queue. - parallel: use the cluster from `cores` to evaluate all calls of indicator functions using the classic R `parallel` back-ends
`mode_args`	list of arguments for the selected `mode`. As of writing this manual, only for the mode `queue` the argument `step` is supported, which gives the number of function calls that are run by one worker at a time. the default is 15, which gives on most of the tested systems a good balance between synchronization overhead and idling workers.

Value

a dataquieR_resultset2. Can be printed creating a RMarkdown-report.

Other reporting_functions: util_alias2caption(), util_copy_all_deps(), util_create_page_file(), util_eval_to_dataquieR_result(), util_float_index_menu(), util_generate_anchor_link(), util_generate_anchor_tag(), util_generate_calls(), util_generate_calls_for_function(), util_load_manual(), util_make_data_slot_from_table_slot(), util_make_function(), util_order_by_order(), util_set_size()