From 03fedf4642554dff3079a846da6700d29814bbfa Mon Sep 17 00:00:00 2001 From: =?UTF-8?q?zxBIB=20Lech=C3=B3n=2CMiguel=20=28MED=20BDS=29=20EXTERNAL?= Date: Sun, 21 Jul 2024 09:04:31 +0200 Subject: [PATCH] Initial commit. --- .Rbuildignore | 12 + .github/CODEOWNERS | 1 + .github/workflows/ci.yml | 21 + .gitignore | 11 + .lintr.R | 21 + DESCRIPTION | 47 + LICENSE | 13 + NAMESPACE | 14 + NEWS.md | 62 + R/aaa_preface.R | 76 + R/check_papo_call_manual.R | 766 ++++++++++ R/create_plots.R | 259 ++++ R/data_prep.R | 112 ++ R/dressing_room.R | 1251 +++++++++++++++++ R/global_params.r | 16 + R/mock_patient_profile.R | 211 +++ R/mock_with_mm.R | 145 ++ R/mod_API.R | 116 ++ R/mod_listing.R | 222 +++ R/mod_patient_info.R | 61 + R/mod_patient_profile.R | 384 +++++ R/mod_plots.R | 487 +++++++ R/mod_signature.R | 171 +++ R/prep_safety_data.R | 66 + R/utils-misc.R | 65 + R/write_mod_signature.R | 79 ++ README.Rmd | 91 ++ README.md | 88 ++ _pkgdown.yml | 25 + inst/validation/results/.gitempty | 0 inst/validation/run_validation.R | 44 + inst/validation/specs.R | 35 + inst/validation/utils-validation.R | 155 ++ inst/validation/val_report.Rmd | 17 + inst/validation/val_report_child.Rmd | 209 +++ man/cash-.pack_of_constants.Rd | 20 + man/create_ae_cm_plot.Rd | 30 + man/create_lb_vs_plot.Rd | 50 + man/create_vlines.Rd | 22 + man/explorer_app.Rd | 19 + man/figures/demo.png | Bin 0 -> 105707 bytes man/figures/patient_profile_app.png | Bin 0 -> 79563 bytes man/get_labels.Rd | 25 + man/mock_patient_profile_UI.Rd | 18 + man/mock_patient_profile_app.Rd | 13 + man/mock_patient_profile_server.Rd | 15 + man/mock_with_mm_app.Rd | 13 + man/mod_patient_profile.Rd | 280 ++++ man/mod_patient_profile_UI.Rd | 22 + man/mod_patient_profile_params.Rd | 202 +++ man/mod_patient_profile_server.Rd | 204 +++ man/pack_of_constants.Rd | 46 + man/patient_info_UI.Rd | 19 + man/patient_info_server.Rd | 23 + man/patient_listing_UI.Rd | 16 + man/patient_listing_server.Rd | 34 + man/patient_plot_UI.Rd | 18 + man/patient_plot_server.Rd | 23 + man/prep_safety_data.Rd | 20 + man/pt_info_data_filter.Rd | 25 + tests/testthat.R | 6 + tests/testthat/apps/misconfigured_app/app.R | 9 + .../apps/patient_selector_switching/app.R | 129 ++ tests/testthat/apps/root/app.R | 19 + tests/testthat/setup.R | 177 +++ tests/testthat/test-all.R | 350 +++++ vignettes/.gitignore | 2 + vignettes/a00-papo.Rmd | 287 ++++ vignettes/a01-data_requirements.Rmd | 28 + vignettes/a02-communication.Rmd | 45 + vignettes/images/complete_display.jpg | Bin 0 -> 153829 bytes vignettes/images/info.png | Bin 0 -> 46342 bytes vignettes/images/listings.jpg | Bin 0 -> 65124 bytes vignettes/images/plots.jpg | Bin 0 -> 103807 bytes vignettes/images/sample_error.jpg | Bin 0 -> 41509 bytes vignettes/images/summary.jpg | Bin 0 -> 25433 bytes vignettes/qc.Rmd | 32 + 77 files changed, 7594 insertions(+) create mode 100644 .Rbuildignore create mode 100644 .github/CODEOWNERS create mode 100644 .github/workflows/ci.yml create mode 100644 .gitignore create mode 100644 .lintr.R create mode 100644 DESCRIPTION create mode 100644 LICENSE create mode 100644 NAMESPACE create mode 100644 NEWS.md create mode 100644 R/aaa_preface.R create mode 100644 R/check_papo_call_manual.R create mode 100644 R/create_plots.R create mode 100644 R/data_prep.R create mode 100644 R/dressing_room.R create mode 100644 R/global_params.r create mode 100644 R/mock_patient_profile.R create mode 100644 R/mock_with_mm.R create mode 100644 R/mod_API.R create mode 100644 R/mod_listing.R create mode 100644 R/mod_patient_info.R create mode 100644 R/mod_patient_profile.R create mode 100644 R/mod_plots.R create mode 100644 R/mod_signature.R create mode 100644 R/prep_safety_data.R create mode 100644 R/utils-misc.R create mode 100644 R/write_mod_signature.R create mode 100644 README.Rmd create mode 100644 _pkgdown.yml create mode 100644 inst/validation/results/.gitempty create mode 100644 inst/validation/run_validation.R create mode 100644 inst/validation/specs.R create mode 100644 inst/validation/utils-validation.R create mode 100644 inst/validation/val_report.Rmd create mode 100644 inst/validation/val_report_child.Rmd create mode 100644 man/cash-.pack_of_constants.Rd create mode 100644 man/create_ae_cm_plot.Rd create mode 100644 man/create_lb_vs_plot.Rd create mode 100644 man/create_vlines.Rd create mode 100644 man/explorer_app.Rd create mode 100644 man/figures/demo.png create mode 100644 man/figures/patient_profile_app.png create mode 100644 man/get_labels.Rd create mode 100644 man/mock_patient_profile_UI.Rd create mode 100644 man/mock_patient_profile_app.Rd create mode 100644 man/mock_patient_profile_server.Rd create mode 100644 man/mock_with_mm_app.Rd create mode 100644 man/mod_patient_profile.Rd create mode 100644 man/mod_patient_profile_UI.Rd create mode 100644 man/mod_patient_profile_params.Rd create mode 100644 man/mod_patient_profile_server.Rd create mode 100644 man/pack_of_constants.Rd create mode 100644 man/patient_info_UI.Rd create mode 100644 man/patient_info_server.Rd create mode 100644 man/patient_listing_UI.Rd create mode 100644 man/patient_listing_server.Rd create mode 100644 man/patient_plot_UI.Rd create mode 100644 man/patient_plot_server.Rd create mode 100644 man/prep_safety_data.Rd create mode 100644 man/pt_info_data_filter.Rd create mode 100644 tests/testthat.R create mode 100644 tests/testthat/apps/misconfigured_app/app.R create mode 100644 tests/testthat/apps/patient_selector_switching/app.R create mode 100644 tests/testthat/apps/root/app.R create mode 100644 tests/testthat/setup.R create mode 100644 tests/testthat/test-all.R create mode 100644 vignettes/.gitignore create mode 100644 vignettes/a00-papo.Rmd create mode 100644 vignettes/a01-data_requirements.Rmd create mode 100644 vignettes/a02-communication.Rmd create mode 100644 vignettes/images/complete_display.jpg create mode 100644 vignettes/images/info.png create mode 100644 vignettes/images/listings.jpg create mode 100644 vignettes/images/plots.jpg create mode 100644 vignettes/images/sample_error.jpg create mode 100644 vignettes/images/summary.jpg create mode 100644 vignettes/qc.Rmd diff --git a/.Rbuildignore b/.Rbuildignore new file mode 100644 index 0000000..ebe3985 --- /dev/null +++ b/.Rbuildignore @@ -0,0 +1,12 @@ +R/write_mod_signature.R +.*Rproj +^\.Rproj\.user$ +^LICENSE$ +^LICENSE\.md$ +^README\.Rmd$ +^_pkgdown\.yml$ +^docs$ +^pkgdown$ +.lintr +_tests_ +^.*\.Rproj$ diff --git a/.github/CODEOWNERS b/.github/CODEOWNERS new file mode 100644 index 0000000..3817383 --- /dev/null +++ b/.github/CODEOWNERS @@ -0,0 +1 @@ +* @boehringer-ingelheim/davinci diff --git a/.github/workflows/ci.yml b/.github/workflows/ci.yml new file mode 100644 index 0000000..d5060a1 --- /dev/null +++ b/.github/workflows/ci.yml @@ -0,0 +1,21 @@ +--- +name: Checks 🧩 + +on: + pull_request: + types: + - opened + - synchronize + - reopened + - ready_for_review + branches: + - main + push: + branches: + - main + workflow_dispatch: + +jobs: + run-shared-ci: + name: Shared + uses: boehringer-ingelheim/dv.templates/.github/workflows/shared_ci.yml@main diff --git a/.gitignore b/.gitignore new file mode 100644 index 0000000..3d73374 --- /dev/null +++ b/.gitignore @@ -0,0 +1,11 @@ +.vscode +.Rproj.user +.Rhistory +*.Rproj +*.swp +*.sh +.vimlocal +docs +shiny_bookmarks +inst/validation/validation_report.html +tests/test-out.xml diff --git a/.lintr.R b/.lintr.R new file mode 100644 index 0000000..59d002c --- /dev/null +++ b/.lintr.R @@ -0,0 +1,21 @@ +linters <- lintr::default_linters # -[ diff with dv.templates 3ca8d7a10cfc7ad2307644dcac603e1f1f0feb72]- +linters <- lintr::modify_defaults( + linters + , line_length_linter = NULL # we see how long lines are when we write them + , indentation_linter = NULL + , trailing_whitespace_linter = NULL + , cyclocomp_linter = NULL # prevents trivial amount of nesting and long but straightforward functions + , object_name_linter = NULL # we have reasons to capitalize. nobody in our team CamelCase. shiny does + , object_length_linter = NULL # we don't type long var names just because + , pipe_continuation_linter = NULL # wickham being overly prescriptive + , trailing_blank_lines_linter = NULL # natural extension of trailing_whitespace_linter, present on the template +) + +if(identical(Sys.getenv('CI'), "true")){ + linters <- lintr::modify_defaults( + linters + , object_usage_linter = NULL # R lacks var declarations; it's easy to assign to the wrong variable by mistake + ) # We only disable this lint rule on github because it fails there because +} # of a long-standing lintr bug + +linters \ No newline at end of file diff --git a/DESCRIPTION b/DESCRIPTION new file mode 100644 index 0000000..5362648 --- /dev/null +++ b/DESCRIPTION @@ -0,0 +1,47 @@ +Package: dv.papo +Title: Patient Profile +Version: 2.0.0 +Date: 2024-07-02 +Authors@R: + c(person("Boehringer-Ingelheim Pharma GmbH & Co.KG", role = c("cph", "fnd")), + person(given = "Korbinian", + family = "Matthias", + role = c("cre"), + email = "korbinian.matthias@boehringer-ingelheim.com"), + person(given = "Miguel", + family = "Lechón", + role = c("aut"), + email = "miguel.lechon.ext@boehringer-ingelheim.com"), + person(given = "Yuzheng", + family = "Ou", + role = "aut") + ) +Description: Patient Profile Module. +License: Apache License (>= 2) +Encoding: UTF-8 +LazyData: true +Roxygen: list(markdown = TRUE) +RoxygenNote: 7.3.0 +Depends: + R (>= 4.1.0) +Imports: + checkmate, + DT, + ggplot2, + plotly, + rlang, + shiny, + shinyWidgets, + fontawesome +Suggests: + dv.manager (>= 2.1.0), + knitr, + safetyData, + shinytest2, + testthat, + jsonlite, + withr, + dplyr +Remotes: boehringer-ingelheim/dv.manager@main +VignetteBuilder: knitr +Config/testthat/edition: 3 diff --git a/LICENSE b/LICENSE new file mode 100644 index 0000000..d3ecea3 --- /dev/null +++ b/LICENSE @@ -0,0 +1,13 @@ +Copyright 2024 Boehringer-Ingelheim Pharma GmbH & Co.KG + +Licensed under the Apache License, Version 2.0 (the "License"); +you may not use this file except in compliance with the License. +You may obtain a copy of the License at + + http://www.apache.org/licenses/LICENSE-2.0 + +Unless required by applicable law or agreed to in writing, software +distributed under the License is distributed on an "AS IS" BASIS, +WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +See the License for the specific language governing permissions and +limitations under the License. diff --git a/NAMESPACE b/NAMESPACE new file mode 100644 index 0000000..41d2b92 --- /dev/null +++ b/NAMESPACE @@ -0,0 +1,14 @@ +# Generated by roxygen2: do not edit by hand + +S3method("$",pack_of_constants) +S3method("[",pack_of_constants) +S3method("[[",pack_of_constants) +export(explorer_app) +export(mock_patient_profile_UI) +export(mock_patient_profile_app) +export(mock_patient_profile_server) +export(mock_with_mm_app) +export(mod_patient_profile) +export(mod_patient_profile_UI) +export(mod_patient_profile_server) +importFrom(rlang,.data) diff --git a/NEWS.md b/NEWS.md new file mode 100644 index 0000000..585eb27 --- /dev/null +++ b/NEWS.md @@ -0,0 +1,62 @@ +# dv.papo 2.0.0 + +- Major API redesign with the following breaking changes `mod_patient_profile()`: + - The name of the subject-level dataset is now explicitly provided through the `subject_level_dataset_name` parameter. + - `key` has been renamed to `subjid_var`. + - `pt_info` is now called `summary` and has been simplified. It only allows to specify a _single_ dataframe + from which to select columns. Its `row_item` submember has been renamed to `column_count`. + - `tables` is now called `listings` and is a named list of pairs of `dataset` and `default_vars`. This allows + control over which columns are shown by default for each dataset. + - The legacy `basic_info`, `vlines` and `plots` are all now collected under a single `plots` parameter. They have been + restructured for clarity and are also accompanied by a `palette` field that makes it possible for the caller to + specify individual colors. See the main vignette for more information. + - All parameters referring to Study Days have been reframed to point to absolute days. This ensures consistency of the + time axis of plots. + - The module now accepts datetimes as well as dates for easier joint configuration with `dv.clinlines`. The "time" + part of datetimes is simply discarded. + - Configuration helper functions have been removed in favor of documentation templates. + - `jumping_vars` is now called `sender_ids` for consistency across davinci modules. + +- The module is now easier to configure because it: + - Makes all of its main three sections (`summary`, `listings` and `plots`) optional, which facilitates having a base + working configuration. + - Provides clear start-up warnings and messages when the module is misconfigured with respect to input datasets. + The app creator can safely assume that if no such message appears, the module will not misbehave when interacted + with due to misconfiguration. Any remaining error rests solely on the module developer's shoulders or on those of + the platform provider. + +- Bug fixes: + - Day labels now follow the standard CDISC behavior of skipping day 0 on plots (day 1 refers to the Treatment Start + Date; day -1 is the day before). + - Vertical lines now cross all plots. + + +# dv.papo 1.0.2 + +- bugfix: With the new version of dv.filter 2.1.0 the patient selector did not work. This is now fixed. + +# dv.papo 1.0.1 + +- bugfix: Updating patient selector after jumping from another module didn't work. This is now fixed. + +# dv.papo 1.0.0 + +- Primary interface: `mod_patient_profile()` + +- Launch mock app for demo and testing via `mock_with_mm_app()` + +- Enables bookmarking state of Shiny app via URL + +# dv.papo 0.1 + +* Plot section added. + +# dv.papo 0.0.2 + +* Shinydashboard element removed. + +# dv.papo 0.0.1 + +* Added a `NEWS.md` file to track changes to the package. + + diff --git a/R/aaa_preface.R b/R/aaa_preface.R new file mode 100644 index 0000000..3f4b78f --- /dev/null +++ b/R/aaa_preface.R @@ -0,0 +1,76 @@ +# THIS FILE IS NAMED aaa_preface.R SO IT IS LOADED BEFORE ALL OTHER FILES +# DO NOT CHANGE ITS NAME. IT MUST BE THE FIRST ONE ALPHABETICALLY. + +#' Build a collection of named constants +#' +#' @param ... Named parameters to be collected as constants +#' +#' @keywords internal +#' +#' @details +#' Shiny uses strings as IDs to link UI and server elements. E.g: +#' foo_UI(id = ns("foo")) ... +#' foo_server(id = "foo") +#' +#' This pattern makes it easy for programmers to fall on the trap of modifying one instance of the string literal "foo" +#' without modifying the rest and be unaware of the problem until a bug is hit. It's also easy to mistakes uses of "foo" +#' as an identifier from other uses (text labels, ...) when, as it's often the case, the parameter is not explicitly +#' named. +#' One easy fix consists in using global variables instead of plain string literals. In the case of the previous +#' example, that would mean: +#' ID_FOO <- "foo" +#' foo_UI(ns(ID_FOO)) ... +#' foo_server(ID_FOO) +#' +#' That simple addition makes the purpose of ID_FOO clear and also fails gracefully when not all ID_FOO instances are +#' updated synchronously along a codebase. It has the drawback of polluting the global namespace with identifier +#' variables. That's easily solved by creating a container of constants, which is the purpose of this pack_of_constants +#' alias. +#' ID <- pack_of_constants(FOO = "foo", BAR = "bar") +#' ID$FOO +#' "foo" +#' ID$BA +#' Error in `$.pack_of_constants`(ID, BA) : +#' Pack of constants "ID" does not contain "BA" +#' +#' The pack of constants is a plain named list that enforces that all elements have unique, non-null names. +#' It is tagged as an S3 object to override its extraction operators. +#' +#' The use of checkmate is unnecessary, but it's a Good Library(TM) and your module should rely on it anyways +pack_of_constants <- function(...) { + result <- list(...) + checkmate::assert_list(result, any.missing = FALSE, names = "unique") + class(result) <- c("pack_of_constants", class(result)) + result +} + +#' Extract constant from pack +#' +#' @param pack pack_of_constants +#' @param name target constant +#' +#' This function differs from the base list extraction method in that it avoids partial matching of keys and throws +#' an error if the looked-for constant is not contained within the pack. +#' +#' @keywords internal +#' +#' @export +`$.pack_of_constants` <- function(pack, name) { + checkmate::assert_true(name %in% names(pack), .var.name = paste0(deparse(substitute(pack)), "$", name)) + NextMethod() +} + +# This exports are recent requirement for devtools check https://github.com/r-lib/roxygen2/issues/1592#issue-2121199122 +#' +#' @keywords internal +#' +#' @export +`[[.pack_of_constants` <- `$.pack_of_constants` + +#' @keywords internal +#' @export +`[.pack_of_constants` <- function(pack, name) { + stop("Invalid pack_of_constants method") +} + +poc <- pack_of_constants diff --git a/R/check_papo_call_manual.R b/R/check_papo_call_manual.R new file mode 100644 index 0000000..0f5526f --- /dev/null +++ b/R/check_papo_call_manual.R @@ -0,0 +1,766 @@ +# nolint start object_usage_linter + +# TODO: Generate from mod_patient_profile_API +# This function has been written manually, but mod_patient_profile_API carries +# enough information to derive most of it automatically +check_papo_call <- function(datasets, module_id, subject_level_dataset_name, subjid_var, + sender_ids, summary, listings, plots) { + warn <- character(0) + err <- character(0) + + assert_warn <- function(cond, msg, do_assert = TRUE) { + ok <- FALSE + if (isTRUE(do_assert)) { + ok <- isTRUE(cond) + if (!ok) warn <<- c(warn, msg) + } + return(ok) + } + + assert_err <- function(cond, msg, do_assert = TRUE) { + ok <- FALSE + if (isTRUE(do_assert)) { + ok <- isTRUE(cond) + if (!ok) err <<- c(err, paste0(msg, ".")) + } + return(ok) + } + + is_valid_shiny_id <- function(s) grepl("^$|^[a-zA-Z][a-zA-Z0-9_-]*$", s) + + is_date_lower_or_equal <- function(a, b) all(as.POSIXct(a) <= as.POSIXct(b), na.rm = TRUE) + + allowed_classes_logical <- c("logical") + allowed_classes_character <- c("character") + allowed_classes_character_factor <- c("character", "factor") + allowed_classes_numeric <- c("integer", "numeric") + allowed_classes_date <- c("Date", "POSIXt") + + afmm_datasets <- paste(names(datasets), collapse = ", ") + + used_dataset_names <- list() # name identifies parameter, value stores dataset name + + # module_id + assert_err(!missing(module_id), "`module_id` missing") && + assert_err(checkmate::test_string(module_id), "`module_id` should be a string") && + assert_warn(nchar(module_id) > 0, "Consider providing a non-empty `module_id`.") && + assert_err( + is_valid_shiny_id(module_id), + paste( + "`module_id` should be a valid identifier, starting with a letter and followed by", + "alphanumeric characters, hyphens and underscores" + ) + ) + + # subject_level_dataset_name + sl_dataset_ok <- ( + assert_err(!missing(subject_level_dataset_name), "`subject_level_dataset_name` missing") && + assert_err( + checkmate::test_string(subject_level_dataset_name, min.chars = 1), + "`subject_level_dataset_name` should be a non-empty string" + ) && + assert_err( + subject_level_dataset_name %in% names(datasets), + paste( + "`subject_level_dataset_name` does not refer to any of the available datasets:", + afmm_datasets + ) + ) + ) + if (sl_dataset_ok) { + used_dataset_names[["subject_level_dataset_name"]] <- subject_level_dataset_name + } + + # subjid_var + subjid_var_ok <- ( + assert_err(!missing(subjid_var), "`subjid_var` missing") && + assert_err(checkmate::test_string(subjid_var, min.chars = 1), "`subjid_var` should be a non-empty string") && + sl_dataset_ok + ) + + if (subjid_var_ok) { + dataset <- datasets[[subject_level_dataset_name]] + assert_err(subjid_var %in% names(dataset), "`subjid_var` not a column of `subject_level_dataset_name`") + assert_err( + !any(duplicated(dataset[[subjid_var]])), + sprintf( + "`subjid_var` (%s) does not uniquely identify rows of `subject_level_dataset_name` (%s)", + subjid_var, subject_level_dataset_name + ) + ) + } + + # TODO: sender_ids + + # summary + if (!missing(summary) && !is.null(summary)) { + if (assert_err(checkmate::test_list(summary, names = "unique"), "`summary` should be a named list")) { + if (sl_dataset_ok && assert_err("vars" %in% names(summary), "`summary` is missing element `vars`") && + assert_err( + checkmate::test_character(summary[["vars"]], null.ok = FALSE), + "`summary$vars` should be a non-empty character vector" + )) { + dataset <- datasets[[subject_level_dataset_name]] + excess_cols <- setdiff(summary[["vars"]], names(dataset)) + assert_err( + length(excess_cols) == 0, + sprintf( + "`summary$vars` refers to unknown dataset variables (%s)", + paste(excess_cols, collapse = ", ") + ) + ) + } + + if (assert_err("column_count" %in% names(summary), "`summary` is missing element `column_count`")) { + assert_err( + checkmate::test_int(summary[["column_count"]], lower = 1, upper = 12), + "`summary$column_count` is not a single integer in the [1, 12] range" + ) + } + } + } + + # listings + if (!missing(listings) && !is.null(listings)) { + if (assert_err(checkmate::test_list(listings, names = "unique", min.len = 1), "`listings` must be a non-empty named list")) { + for (i_listing in seq_along(listings)) { + listing <- listings[[i_listing]] + listing_name <- names(listings)[[i_listing]] + + code_ref <- sprintf("listings[['%s']]", listing_name) + + if (assert_err( + checkmate::test_list(listing, names = "unique"), + sprintf("`%s` is not a named list. ", code_ref) + )) { + # listing$dataset + if (assert_err( + "dataset" %in% names(listing), + sprintf("`%s` is missing element `dataset`", code_ref) + ) && + assert_err( + checkmate::test_string(listing[["dataset"]], min.chars = 1), + sprintf("`%s$dataset` should be a non-empty string", code_ref) + ) && + assert_err( + listing[["dataset"]] %in% names(datasets), + sprintf( + "`%s$dataset` (%s) does not refer to any of the available datasets (%s)", + code_ref, listing[["dataset"]], afmm_datasets + ) + )) { + dataset_name <- listing[["dataset"]] + used_dataset_names[[sprintf("listings[[%d]]$dataset_name", i_listing)]] <- listing[["dataset"]] + + # listing$default_vars + if ("default_vars" %in% names(listing)) { + default_vars <- listing[["default_vars"]] + if (assert_err( + checkmate::test_character(default_vars, null.ok = TRUE), + sprintf("`%s$default_vars` should be a character vector", code_ref) + )) { + dataset <- datasets[[dataset_name]] + excess_cols <- setdiff(default_vars, names(dataset)) + assert_err( + length(excess_cols) == 0, + sprintf( + "`%s$default_vars` refers to unknown dataset variables (%s)", + code_ref, paste(excess_cols, collapse = ", ") + ) + ) + } + } + } + } + } + } + } + + if (!missing(plots) && !is.null(plots)) { + timeline_info <- plots[["timeline_info"]] + vline_vars <- plots[["vline_vars"]] + vline_day_numbers <- plots[["vline_day_numbers"]] + palette <- plots[["palette"]] + range_plots <- plots[["range_plots"]] + value_plots <- plots[["value_plots"]] + + # timeline_info + if (assert_err( + checkmate::test_character(timeline_info, names = "unique"), + "`plots$timeline_info` must be a named character vector" + )) { + timeline_col_names <- names(timeline_info) + timeline_info_cols_compulsory <- c("trt_start_date", "trt_end_date") + timeline_info_cols_optional <- c("icf_date", "part_end_date") + + missing_cols <- setdiff(timeline_info_cols_compulsory, timeline_col_names) + excess_cols <- setdiff(timeline_col_names, c(timeline_info_cols_compulsory, timeline_info_cols_optional)) + if (assert_err( + length(missing_cols) == 0, + sprintf("`plots$timeline_info` is missing elements %s", paste(missing_cols, ", ")) + ) && + assert_err( + length(excess_cols) == 0, + sprintf("`plots$timeline_info` has excess elements %s", paste(excess_cols, ", ")) + )) { + sl_dataset <- datasets[[subject_level_dataset_name]] + + # NOTE: Repetitions in this section are intentional. In this form they're an easier target for code generation. + + # timeline_info$icf_date + icf_date_ok <- FALSE + if ("icf_date" %in% names(timeline_info)) { + col <- timeline_info[["icf_date"]] + icf_date_ok <- + assert_err( + col %in% names(sl_dataset), + sprintf( + "`plots$timeline_info$%s` refers to column %s, which is not part of subject-level dataset %s", + "icf_date", col, subject_level_dataset_name + ) + ) && + assert_err( + inherits(sl_dataset[[col]], allowed_classes_date), + sprintf( + "`plots$timeline_info$%s` (%s) is not of allowed types (%s)", + "icf_date", col, paste(allowed_classes_date, collapse = ",") + ) + ) + } + # timeline_info$trt_start_date + col <- timeline_info[["trt_start_date"]] + start_date_ok <- + assert_err( + col %in% names(sl_dataset), + sprintf( + "`plots$timeline_info$%s` refers to column %s, which is not part of subject-level dataset %s", + "trt_start_date", col, subject_level_dataset_name + ) + ) && + assert_err( + inherits(sl_dataset[[col]], allowed_classes_date), + sprintf( + "`plots$timeline_info$%s` (%s) is not of allowed types (%s)", + "trt_start_date", col, paste(allowed_classes_date, collapse = ",") + ) + ) + # timeline_info$trt_end_date + col <- timeline_info[["trt_end_date"]] + end_date_ok <- + assert_err( + col %in% names(sl_dataset), + sprintf( + "`plots$timeline_info$%s` refers to column %s, which is not part of subject-level dataset %s", + "trt_end_date", col, subject_level_dataset_name + ) + ) && + assert_err( + inherits(sl_dataset[[col]], allowed_classes_date), + sprintf( + "`plots$timeline_info$%s` (%s) is not of allowed types (%s)", + "trt_end_date", col, paste(allowed_classes_date, collapse = ",") + ) + ) + # timeline_info$part_end_date + part_end_date_ok <- FALSE + if ("part_end_date" %in% names(timeline_info)) { + col <- timeline_info[["part_end_date"]] + part_end_date_ok <- + assert_err( + col %in% names(sl_dataset), + sprintf( + "`plots$timeline_info$%s` refers to column %s, which is not part of subject-level dataset %s", + "part_end_date", col, subject_level_dataset_name + ) + ) && + assert_err( + inherits(sl_dataset[[col]], allowed_classes_date), + sprintf( + "`plots$timeline_info$%s` (%s) is not of allowed types (%s)", + "part_end_date", col, paste(allowed_classes_date, collapse = ",") + ) + ) + } + + # Relationship between timeline vars (icf < start < end < part_end) + if (icf_date_ok && start_date_ok) { + assert_err( + is_date_lower_or_equal(sl_dataset[[timeline_info[["icf_date"]]]], sl_dataset[[timeline_info[["trt_start_date"]]]]), + sprintf( + "Contents of `plots$timeline_info` column %s (%s) should be lesser than or equal to those of column %s (%s)", + "icf_date", timeline_info[["icf_date"]], "trt_start_date", timeline_info[["trt_start_date"]] + ) + ) + } + + if (start_date_ok && end_date_ok) { + assert_err( + timeline_info[["trt_start_date"]] != timeline_info[["trt_end_date"]], + sprintf( + "`plots$timeline_info$%s` and `plots$timeline_info$%s` refer to the same dataset variable (%s)", + "trt_start_date", "trt_end_date", timeline_info[["trt_start_date"]] + ) + ) && + assert_err( + is_date_lower_or_equal(sl_dataset[[timeline_info[["trt_start_date"]]]], sl_dataset[[timeline_info[["trt_end_date"]]]]), + sprintf( + "Contents of `plots$timeline_info$%s` (%s) should be lesser than or equal to those of column %s (%s)", + "trt_start_date", timeline_info[["trt_start_date"]], "trt_end_date", timeline_info[["trt_end_date"]] + ) + ) + } + + if (end_date_ok && part_end_date_ok) { + assert_err( + is_date_lower_or_equal(sl_dataset[[timeline_info[["trt_end_date"]]]], sl_dataset[[timeline_info[["part_end_date"]]]]), + sprintf( + "Contents of `plots$timeline_info` column %s (%s) should be lesser than or equal to those of column %s (%s)", + "trt_end_date", timeline_info[["trt_end_date"]], "part_end_date", timeline_info[["part_end_date"]] + ) + ) + } + } + } + + # range_plots + if (assert_err(checkmate::test_list(range_plots, names = "unique"), "`plots$range_plots` must be a named list")) { + # [[i]] + for (i_plot in seq_along(range_plots)) { + plot_name <- names(range_plots)[[i_plot]] + plot <- range_plots[[i_plot]] + if (assert_err( + setequal(names(plot), c("dataset", "vars", "tooltip")), + "`plots$range_plots` needs exactly three children: `dataset`, `vars` and `tooltip`" + ) && + assert_err( + checkmate::test_string(plot[["dataset"]], min.chars = 1), + sprintf("Field `dataset` in `plots$range_plots` element (%s) should be a non-empty string", plot_name) + ) && + assert_err( + plot[["dataset"]] %in% names(datasets), + sprintf( + "Field `dataset` in `plots$range_plots` element (%s) does not refer to any of the available datasets: %s", + plot_name, paste(names(datasets), collapse = ", ") + ) + )) { + dataset_name <- plot[["dataset"]] + + used_dataset_names[[sprintf("plots$range_plots[[`%s`]]$dataset", plot_name)]] <- dataset_name + + dataset <- datasets[[dataset_name]] + + code_ref <- sprintf('plots$range_plots[["%s"]]', plot_name) + + # range_plots[[i]]$vars + vars <- plot[["vars"]] + if (assert_err( + checkmate::test_character(vars, names = "unique"), + sprintf("`%s$vars` must be a named character vector", code_ref) + )) { + var_col_names <- names(vars) + + range_plot_cols_compulsory <- c("start_date", "end_date", "decode") + range_plot_cols_optional <- c("grading", "serious_ae") + + missing_cols <- setdiff(range_plot_cols_compulsory, var_col_names) + excess_cols <- setdiff(var_col_names, c(range_plot_cols_compulsory, range_plot_cols_optional)) + if (assert_err( + length(missing_cols) == 0, + sprintf("`%s$vars` is missing elements: %s", code_ref, paste(missing_cols, collapse = ", ")) + ) && + assert_err( + length(excess_cols) == 0, + sprintf("`%s$vars` has excess elements: %s", code_ref, paste(excess_cols, collapse = ", ")) + )) { + + # range_plots[[i]]$vars$start_date + col <- vars[["start_date"]] + start_date_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$start_date` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_date), + sprintf( + "`%s$vars$start_date` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_date, collapse = ", ") + ) + ) + # range_plots[[i]]$vars$end_date + col <- vars[["end_date"]] + end_date_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$end_date` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_date), + sprintf( + "`%s$vars$end_date` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_date, collapse = ", ") + ) + ) + # range_plots[[i]]$vars$decode + col <- vars[["decode"]] + decode_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$decode` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_character_factor), + sprintf( + "`%s$vars$decode` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_character_factor, collapse = ", ") + ) + ) + # range_plots[[i]]$vars$grading + if ("grading" %in% names(vars)) { + col <- vars[["grading"]] + grading_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$grading` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_character_factor), + sprintf( + "`%s$vars$grading` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_character_factor, collapse = ", ") + ) + ) + } + # range_plots[[i]]$vars$serious_ae + if ("serious_ae" %in% names(vars)) { + col <- vars[["serious_ae"]] + + kind <- T_or(T_logical(), T_YN()) + serious_ae_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$serious_ae` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + T_is_of_kind(dataset[[col]], kind), + sprintf( + "`%s$vars$serious_ae` column values (%s) are not of allowed types (%s)", + code_ref, col, T_get_type_as_text(kind) + ) + ) + } + + if (start_date_ok && end_date_ok) { + assert_err( + vars[["start_date"]] != vars[["end_date"]], + sprintf( + "`%s$vars$%s` and `plots$range_plots[['%s']]$vars$%s` refer to the same dataset variable (%s)", + code_ref, "start_date", plot_name, "end_date", vars[["start_date"]] + ) + ) && + assert_err( + is_date_lower_or_equal(dataset[[vars[["start_date"]]]], dataset[[vars[["end_date"]]]]), + sprintf( + "Contents of `%s$vars$%s` (%s) should be lesser than or equal to those of column %s (%s)", + code_ref, "start_date", vars[["start_date"]], "end_date", vars[["end_date"]] + ) + ) + } + } + } + + tooltip <- plot[["tooltip"]] + if (assert_err( + checkmate::test_character(tooltip, names = "named", null.ok = TRUE), + sprintf("`%s$tooltip` must be a named character vector", code_ref) + )) { + for (i_tooltip in seq_along(tooltip)) { + col <- tooltip[[i_tooltip]] + assert_err( + col %in% names(dataset), + sprintf( + '`%s$tooltip[[%d]]` refers to column "%s", which is not part of dataset %s', + code_ref, i_tooltip, col, dataset_name + ) + ) + } + } + } + } + } + + if (assert_err(checkmate::test_list(value_plots, names = "unique"), "`plots$value_plots` must be a named list")) { + # [[i]] + for (i_plot in seq_along(value_plots)) { + plot_name <- names(value_plots)[[i_plot]] + plot <- value_plots[[i_plot]] + if (assert_err( + setequal(names(plot), c("dataset", "vars", "tooltip")), + "`plots$value_plots` needs exactly three children: `dataset`, `vars` and `tooltip`" + ) && + assert_err( + checkmate::test_string(plot[["dataset"]], min.chars = 1), + sprintf(sprintf('`plots$value_plots[["%s"]]$dataset` should be a non-empty string', plot_name)) + ) && + assert_err( + plot[["dataset"]] %in% names(datasets), + sprintf( + '`plots$value_plots[["%s"]]$dataset` does not refer to any of the available datasets: %s', + plot_name, paste(names(datasets), collapse = ", ") + ) + )) { + dataset_name <- plot[["dataset"]] + used_dataset_names[[sprintf("`plots$value_plots[[`%s`]]$dataset`", plot_name)]] <- dataset_name + dataset <- datasets[[dataset_name]] + + code_ref <- sprintf('`plots$value_plots[["%s"]]`', plot_name) + + # value_plots[[i]]$vars + vars <- plot[["vars"]] + if (assert_err( + checkmate::test_character(vars, names = "unique"), + "Field `vars` in `plots$value_plots` element (%s) must be a named character vector" + )) { + var_col_names <- names(vars) + + value_plot_cols_compulsory <- c("analysis_param", "analysis_val", "analysis_date") + value_plot_cols_optional <- c("range_low_limit", "range_high_limit", "analysis_indicator", "summary_stats") + + missing_cols <- setdiff(value_plot_cols_compulsory, var_col_names) + excess_cols <- setdiff(var_col_names, c(value_plot_cols_compulsory, value_plot_cols_optional)) + if (assert_err( + length(missing_cols) == 0, + sprintf("`%s$vars` is missing elements: %s", code_ref, paste(missing_cols, collapse = ", ")) + ) && + assert_err( + length(excess_cols) == 0, + sprintf("`%s$vars` has excess elements: %s", code_ref, paste(excess_cols, collapse = ", ")) + )) { + + # value_plots[[i]]$vars$analysis_param + col <- vars[["analysis_param"]] + analysis_param_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$analysis_param` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_character_factor), + sprintf( + "`%s$vars$analysis_param` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_character_factor, collapse = ", ") + ) + ) + # value_plots[[i]]$vars$analysis_val + col <- vars[["analysis_val"]] + analysis_val_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$analysis_val` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_numeric), + sprintf( + "`%s$vars$analysis_val` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_numeric, collapse = ", ") + ) + ) + # value_plots[[i]]$vars$analysis_date + col <- vars[["analysis_date"]] + analysis_date_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$analysis_date` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_date), + sprintf( + "`%s$vars$analysis_date` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_date, collapse = ", ") + ) + ) + # value_plots[[i]]$vars$analysis_indicator + if ("analysis_indicator" %in% names(vars)) { + col <- vars[["analysis_indicator"]] + analysis_indicator_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$analysis_indicator` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_character_factor), + sprintf( + "`%s$vars$analysis_indicator` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_character_factor, collapse = ", ") + ) + ) + } + # value_plots[[i]]$vars$range_low_limit + range_low_limit_ok <- FALSE + if ("range_low_limit" %in% names(vars)) { + col <- vars[["range_low_limit"]] + range_low_limit_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$range_low_limit refers` to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_numeric), + sprintf( + "`%s$vars$range_low_limit` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_numeric, collapse = ", ") + ) + ) + } + + # value_plots[[i]]$vars$range_high_limit + range_high_limit_ok <- FALSE + if ("range_high_limit" %in% names(vars)) { + col <- vars[["range_high_limit"]] + range_high_limit_ok <- + assert_err( + col %in% names(dataset), + sprintf( + "`%s$vars$range_high_limit` refers to column %s, which is not part of dataset %s", + code_ref, col, dataset_name + ) + ) && + assert_err( + inherits(dataset[[col]], allowed_classes_numeric), + sprintf( + "`%s$vars$range_high_limit` column values (%s) are not of allowed types (%s)", + code_ref, col, paste(allowed_classes_numeric, collapse = ", ") + ) + ) + } + + # value_plots[[i]]$vars$summary_stats # TODO + + if (range_low_limit_ok && range_high_limit_ok) { + assert_err( + vars[["range_low_limit"]] != vars[["range_high_limit"]], + sprintf( + "`%s$vars$%s` and `%s$vars$%s` refer to the same dataset variable (%s)", + code_ref, "range_low_limit", code_ref, "range_high_limit", vars[["range_low_limit"]] + ) + ) && + assert_err( + all(dataset[[vars[["range_low_limit"]]]] <= dataset[[vars[["range_high_limit"]]]], na.rm = TRUE), + sprintf( + "Contents of `%s$vars$%s` (%s) should be lesser than or equal to those of `%s$vars$%s` (%s)", + code_ref, "range_low_limit", vars[["range_low_limit"]], code_ref, "range_high_limit", vars[["range_high_limit"]] + ) + ) + } + } + } + + tooltip <- plot[["tooltip"]] + if (assert_err( + checkmate::test_character(tooltip, names = "named", null.ok = TRUE), + sprintf('`plots$value_plots[["%s"]]$tooltip` must be a named character vector', plot_name) + )) { + for (i_tooltip in seq_along(tooltip)) { + col <- tooltip[[i_tooltip]] + assert_err( + col %in% names(dataset), + sprintf( + '`plots$value_plots[["%s"]]$tooltip[[%d]]` refers to column "%s", which is not part of dataset %s', + plot_name, i_tooltip, col, dataset_name + ) + ) + } + } + } + } + } + + # vline_vars + if (assert_err( + checkmate::test_character(vline_vars, names = "named", null.ok = TRUE), + "`plots$vline_vars` must be a named character vector" + )) { + for (i_vline in seq_along(vline_vars)) { + col <- vline_vars[[i_vline]] + assert_err( + col %in% names(sl_dataset), + sprintf( + 'plots$vline_vars[[%d]] refers to column "%s", which is not part of dataset %s', + i_vline, col, subject_level_dataset_name + ) + ) + } + } + + # vline_day_numbers + assert_err( + checkmate::test_integerish(vline_day_numbers, names = "named", null.ok = TRUE), + "`plots$vline_day_numbers` must be a vector of named integers" + ) && + assert_err( + all(vline_day_numbers != 0), + "`plots$vline_day_numbers` must be a valid (non-zero) CDISC Study day" + ) + + # palette + assert_err( + checkmate::test_character(palette, names = "named", null.ok = TRUE) && + all(palette %in% grDevices::colors() | grepl("^#[0-9a-fA-F]{6}$", palette)), + "`plots$palette` must be a vector of named colors" + ) + } + + # subjid_var present in all mentioned datasets + if (subjid_var_ok) { + for (i_dataset in seq_along(used_dataset_names)) { + param <- names(used_dataset_names)[[i_dataset]] + dataset_name <- used_dataset_names[[i_dataset]] + + dataset <- datasets[[dataset_name]] + assert_err( + subjid_var %in% names(dataset), + sprintf( + "Dataset %s (referenced from %s) is missing `subjid_var` column %s", + dataset_name, param, subjid_var + ) + ) + } + } + + res <- list(warnings = warn, errors = err) + + return(res) +} + + +# nolint end diff --git a/R/create_plots.R b/R/create_plots.R new file mode 100644 index 0000000..bdf945a --- /dev/null +++ b/R/create_plots.R @@ -0,0 +1,259 @@ +#' Function to create ae or cm plot +#' +#' @param data Data frame containing the data for the plot +#' @param limits Vector that contains the limits of the plot +#' @param palette Named vector that contains the colors that are used in the plot +#' +#' @keywords internal +#' +#' @return A ggplot2 object +create_ae_cm_plot <- function(data, x_limits, palette, sl_info, vline_vars, vline_day_numbers, + ref_date) { + # set column for title banner + data[["title_banner"]] <- " " + + # NOTE(miguel): The following song and dance courtesy of plotly::layout not supporting dates on axes + + half_day_offset <- 0.5 # Makes it possible to see events that start and end on the same day + + # column names that end with '_z' are days that represent ref_date as zero (unlike CDISC) + data[["start_day_z"]] <- as.numeric(data[["start_date"]] - ref_date) + data[["end_day_z"]] <- as.numeric(data[["end_date"]] - ref_date) + half_day_offset + data[["arrow_left_z"]] <- as.numeric(data[["arrow_left"]] - ref_date) + data[["arrow_right_z"]] <- as.numeric(data[["arrow_right"]] - ref_date) + x_limits_z <- x_limits - ref_date + + grading_available <- "grading" %in% names(data) + grading <- "" + if (grading_available) grading <- data[["grading"]] + + p <- ggplot2::ggplot(data, ggplot2::aes(x = .data[["start_day_z"]], y = .data[["decode"]])) + p <- p + ggplot2::theme_bw() + p <- p + ggplot2::geom_rect(ggplot2::aes( + xmin = .data[["start_day_z"]], + xmax = .data[["end_day_z"]], + ymin = .data[["decode"]], + ymax = .data[["decode"]], + color = grading + ), + size = 3 + ) + + if ("serious_ae" %in% names(data)) { + sae_labels <- ifelse(data[["serious_ae"]], "SAE", "") + p <- p + ggplot2::geom_text(ggplot2::aes( + x = .data[["start_day_z"]], + y = .data[["decode"]], + label = sae_labels + ), + colour = "red", nudge_y = 0.25, nudge_x = 1, size = 3 + ) + } + + # hack to allow hover info at the beginning of the range through transparent dots + p <- p + ggplot2::geom_point(ggplot2::aes( + x = .data[["start_day_z"]], + y = .data[["decode"]], + color = grading + ), + size = 5, alpha = 0, show.legend = FALSE + ) + p <- p + ggplot2::scale_colour_manual(name = "Legend", values = palette) + p <- p + ggplot2::scale_fill_manual(name = "Legend", values = palette) + + if (any(!is.na(data[["arrow_left"]]))) { + p <- p + ggplot2::geom_text(ggplot2::aes( + x = .data[["arrow_left_z"]] - .5, + y = .data[["decode"]], + label = sprintf("\u2190"), + color = grading + ), + size = 10, show.legend = FALSE + ) + } + + if (any(!is.na(data[["arrow_right"]]))) { + p <- p + ggplot2::geom_text(ggplot2::aes( + x = .data[["arrow_right_z"]] + .7, + y = .data[["decode"]], + label = sprintf("\u2192"), + color = grading + ), + size = 10, show.legend = FALSE + ) + } + + p <- p + ggplot2::facet_wrap(~ .data[["title_banner"]], ncol = 1, scales = "free_y") + p <- p + ggplot2::theme( + legend.title = ggplot2::element_blank(), + legend.justification = "top", + legend.position = ifelse(grading_available, "right", "none"), + axis.text.y = ggplot2::element_text(size = 7), + strip.text = ggplot2::element_text(size = 4), + panel.spacing = ggplot2::unit(0, "lines") + ) + + as_CDISC_days <- function(days) days + (days >= 0) + p <- p + ggplot2::scale_x_continuous( + labels = function(days) { + dates <- ref_date + days + days <- as_CDISC_days(days) + sprintf("%s\nDay %s", dates, days) + }, + limits = x_limits_z + ) + + p <- create_vlines(p, sl_info, vline_vars, vline_day_numbers) + + return(p) +} + +#' Function to create lab or vital sign plot +#' +#' @param data Data frame containing the data for the plot +#' @param lb_selected_params Vector containing the values of the selected parameters +#' @param day Character name of the variable that contains the analyze day +#' @param val Character name of the variable that contains analyze value +#' @param low_limit Character name of the variable that contains the values of the low limit of the normal range +#' @param high_limit Character name of the variable that contains the values of the high limit of the normal range +#' @param params Character name of the variable that contains the values of the analyze parameters +#' @param analysis_indicator Character name of the variable that contains the values analysis indicator +#' @param summary_stats Character name of the variable that contains the values of the summary statistic +#' @param limits Vector that contains the limits of the plot +#' +#' @keywords internal +#' +#' @return A ggplot2 object +create_lb_vs_plot <- function(data, date, val, low_limit, high_limit, param, summary_stats, x_limits, + palette, sl_info, vline_vars, vline_day_numbers, ref_date) { + # NOTE(miguel): The following song and dance courtesy of plotly::layout not supporting dates on axes + # column names that end with '_z' are days that represent ref_date as zero (unlike CDISC) + data[["date_z"]] <- as.numeric(as.Date(data[[date]]) - ref_date) + x_limits_z <- x_limits - ref_date + + # initiate plot object + plot <- ggplot2::ggplot(data, ggplot2::aes(x = .data[["date_z"]], y = .data[[val]], group = 1)) + + ggplot2::theme_bw() + + # reference range + if (!is.null(low_limit) && !is.null(high_limit)) { + # TODO: Assert that low and high limits are the same ( maybe even outside this function ? ) + low_limit <- unique(data[[low_limit]])[[1]] + high_limit <- unique(data[[high_limit]])[[1]] + + # Plotly doesn't support ggplot -Inf,+Inf ranges for geom_rect (https://github.com/plotly/plotly.R/issues/1559) + # so we're forced to derive a range ourselves + plot <- plot + + ggplot2::geom_rect(ggplot2::aes( + xmin = x_limits_z[[1]], xmax = x_limits_z[[2]], ymin = low_limit, ymax = high_limit, + fill = "REFERENCE RANGE" + ), alpha = 0.3, inherit.aes = FALSE) + } + + plot <- create_vlines(plot, sl_info, vline_vars, vline_day_numbers) + + + # line or summary line + if (is.null(summary_stats)) { + plot <- plot + ggplot2::geom_line(ggplot2::aes(linetype = .data[[param]]), size = 0.1) + } else { + summary_stats_label <- attr(data[[summary_stats]], "label") + plot <- plot + ggplot2::geom_line(ggplot2::aes( + x = .data[["date_z"]], + y = .data[[summary_stats]], + linetype = summary_stats_label + ), + size = 0.1 + ) + } + + # dots (plain or analysis indicator) + if ("analysis_indicator" %in% names(data)) { + # NOTE: if original order is desired, app creator should provide sorted analysis_indicator factor levels + plot <- plot + ggplot2::geom_point(ggplot2::aes( + color = .data[["analysis_indicator"]], + fill = .data[["analysis_indicator"]] + ), size = 1) + } else { + plot <- plot + ggplot2::geom_point(color = "black", size = 1) + } + + + plot <- plot + ggplot2::scale_color_manual(name = "Legend", values = palette) + plot <- plot + ggplot2::scale_fill_manual(name = "Legend", values = palette) + + as_CDISC_days <- function(days) days + (days >= 0) + + # get facet plots and set formats + plot <- plot + ggplot2::facet_wrap(ggplot2::vars(.data[[param]]), ncol = 1, scales = "free_y") + + ggplot2::theme( + legend.title = ggplot2::element_blank(), # disable legend title + legend.justification = "top", + axis.text.y = ggplot2::element_text(size = 7), # y-axis text size + strip.text = ggplot2::element_text(size = 6), # title text/banner size + panel.spacing.y = ggplot2::unit(0, "lines") # distance between plots in facet_wrap + ) + + ggplot2::xlab("") + ggplot2::ylab("") + + ggplot2::scale_x_continuous( + labels = function(days) { + dates <- ref_date + days + days <- as_CDISC_days(days) + sprintf("%s\nDay %s", dates, days) + }, + limits = x_limits_z + ) + + # HACK: Offset the limits of the y axis to account for label strips + # TODO: Remove during transition away from ggplot2+plotly + data_range <- range(data[[val]]) + range_width <- data_range[[2]] - data_range[[1]] + data_range <- data_range + c(-0.15 * range_width, 0) + plot <- plot + ggplot2::coord_cartesian( + ylim = data_range, expand = TRUE, default = TRUE, clip = "on" + ) + + return(plot) +} + +#' Add vertical lines to plot +#' +#' @param plot A ggplot2 object +#' @param plot_data Data of the plot +#' @param vline_vars A list used to define the label and position of dashed lines in the plots +#' +#' @keywords internal +#' +#' @return A ggplot2 object +create_vlines <- function(plot, plot_data, vline_vars, vline_day_numbers) { + # Days are CDISC-based which means anything >=0 has been incremented by 1, so we undo that + cdisc_to_continuous_day_number <- function(day) day - (day >= 0) + + vline_x_data <- lapply(vline_vars, function(vline) { + if (inherits(plot_data[[vline]], "Date")) { + # The logical space of the plot _does_ use 0 as the reference date, so no transformation is necessary for dates + plot_data[[vline]] - plot_data[["trt_start_date"]] + } else { + if (length(plot_data[[vline]]) > 1) browser() + cdisc_to_continuous_day_number(plot_data[[vline]]) + } + }) + + vline_x_data <- append(vline_x_data, cdisc_to_continuous_day_number(vline_day_numbers)) + + not_null_vline_x_data <- sapply(vline_x_data, function(x) { + !is.null(x) + }) + vline_x_data <- setdiff(vline_x_data, not_null_vline_x_data) + x <- unlist(vline_x_data, use.names = FALSE) + colors <- names(vline_x_data) + + if (length(colors) && length(x)) { # this guard only to prevent ggplotly from failing if on empty vline spec + vline_data <- data.frame(x, colors) + plot <- plot + ggplot2::geom_vline( + data = vline_data, ggplot2::aes(xintercept = x, color = colors), + linetype = "dashed", alpha = 1 + ) + } + + return(plot) +} diff --git a/R/data_prep.R b/R/data_prep.R new file mode 100644 index 0000000..9544c6f --- /dev/null +++ b/R/data_prep.R @@ -0,0 +1,112 @@ +#' Filter datasets for patient information section +#' +#' @inheritParams mod_patient_profile_server +#' @param df TODO +#' @param columns TODO +#' @param selected_key TODO +#' +#' @keywords internal +#' +#' @return A list containing datasets for patient information and plots +pt_info_data_filter <- function(df, subjid_var, columns, selected_key) { + res <- NA + row_index <- which(df[[subjid_var]] == selected_key) + if (length(row_index) == 1) { + res <- df[row_index, columns] + } + + return(res) +} + +#' This function will return corresponding labels in a dataset. +#' @param dataset Dataset to get labels from. +#' @param col_names Vector of character names of the columns in the dataset. +#' @param keep_as_original Logical TRUE or FALSE: If TRUE, the corresponding column with +#' no label will return column name, else return NA. +#' If not assigned, it will return all labels of the the dataset. Otherwise, +#' only labels of corresponding columns will be returned. +#' +#' @keywords internal +#' +#' @return Vector containing the labels of the dataset +get_labels <- function(dataset, col_names = NULL, keep_as_original = FALSE) { + if (is.null(col_names)) { + col_names <- names(dataset) + } + out <- sapply(col_names, function(name) { + if (name %in% names(dataset)) { + label <- attributes(dataset[[name]])$label + if (is.null(label)) { + ifelse(keep_as_original, name, NA) + } else { + label + } + } else { + stop(paste0( + "Column '", name, "' NOT in Dataset: '", + deparse(substitute(dataset)), "'!" + )) + } + }) + + out <- unname(out) + return(out) +} + +flag_columns_shinyvalidate <- function(cols, pre = "", post = "") { + shiny::validate( + shiny::need( + length(cols) == 0, + message = paste(pre, paste0("`", cols, "`", collapse = ", "), post) + ) + ) +} + +flag_columns_capture_error <- function(cols, pre = "", post = "") { + res <- NULL + if (length(cols)) { + res <- paste(pre, paste0("`", cols, "`", collapse = ", "), post) + } + return(res) +} + +ensure_columns_exist <- function(df, cols, flag_column_function = flag_columns_shinyvalidate) { + checkmate::assert_character(cols) + excess_columns <- setdiff(cols, names(df)) + + return(flag_column_function( + excess_columns, + pre = paste( + "dv.papo: Can't find user defined column(s) in the dataset.", + "You've tried to set the following column(s):" + ), + post = "Have you spelled their names correctly?" + )) +} + +ensure_columns_are_dates_or_datetimes <- function(df, cols, flag_column_function = flag_columns_shinyvalidate) { + checkmate::assert_character(cols, null.ok = TRUE) + mask <- sapply(df[cols], function(x) inherits(x, c("Date", "POSIXt"))) + incorrect_cols <- cols[!mask] + return(flag_column_function( + incorrect_cols, + pre = paste( + "dv.papo: Column(s) holding dates must be of type `Date` or `POSIXt`.", + "The following column(s) are not of those types:" + ), + post = r"----(Type "vignette("lubridate")" into your console to learn more about time types.)----" + )) +} + +ensure_columns_are_numeric <- function(df, cols, flag_column_function = flag_columns_shinyvalidate) { + checkmate::assert_character(cols, null.ok = TRUE) + date_mask <- sapply(df[cols], is.numeric) + incorrect_cols <- cols[!date_mask] + return(flag_column_function( + incorrect_cols, + pre = paste( + "dv.papo: Column(s) holding days/values must be of type numeric", + "The following column(s) are not of type numeric:" + ) + )) +} diff --git a/R/dressing_room.R b/R/dressing_room.R new file mode 100644 index 0000000..53141c6 --- /dev/null +++ b/R/dressing_room.R @@ -0,0 +1,1251 @@ +# Ad-hoc type system ---- + +# basic types +T_logical <- function() list(kind = "logical") +T_factor <- function() list(kind = "factor") +T_character <- function() list(kind = "character") +T_date <- function() list(kind = "date") +T_datetime <- function() list(kind = "datetime") +T_integer <- function(min = NA, max = NA) list(kind = "integer", min = min, max = max) # allows numeric if all values are integer +T_numeric <- function(min = NA, max = NA) list(kind = "numeric", min = min, max = max) + +# permissive types +T_anything <- function() list(kind = "anything") + +# sum types +T_or <- function(...) list(kind = "or", options = list(...)) + +# known- and variable-length collections +T_group <- function(...) list(kind = "group", elements = list(...)) + +# domain-specific types +T_mod_ID <- function() list(kind = "mod") +T_dataset_name <- function() list(kind = "dataset_name") +T_col <- function(dataset_name, sub_kind = T_anything()) { + list(kind = "col", dataset_name = dataset_name, sub_kind = sub_kind) +} +T_color <- function() list(kind = "color") +T_CDISC_study_day <- function() list(kind = "cdisc_study_day", min = NA, max = NA) +T_YN <- function() list(kind = "YN") + +T_is_of_kind <- function(var, type) { + res <- FALSE + if (length(type) == 1 && is.na(type)) browser() + + if (type[["kind"]] == "or") { + for (option in type[["options"]]) res <- res || T_is_of_kind(var, option) + } else if (type[["kind"]] == "anything") { + res <- TRUE + } else if (type[["kind"]] == "factor") { + res <- is.factor(var) + } else if (type[["kind"]] == "character") { + res <- is.character(var) + } else if (type[["kind"]] == "date") { + res <- inherits(var, "Date") + } else if (type[["kind"]] == "datetime") { + res <- inherits(var, "POSIXt") + } else if (type[["kind"]] == "numeric") { + res <- is.numeric(var) + } else if (type[["kind"]] == "integer") { + res <- is.integer(var) || (is.numeric(var) && all(var[is.finite(var)] %% 1 == 0)) + } else if (type[["kind"]] == "logical") { + res <- is.logical(var) + } else if (type[["kind"]] == "cdisc_study_day") { + res <- (is.integer(var) || (is.numeric(var) && all(var[is.finite(var)] %% 1 == 0))) && all(var[is.finite(var)] != 0) + } else if (type[["kind"]] == "YN") { + res <- ((is.character(var) && setequal(unique(var), c("Y", "N"))) || + is.factor(var) && setequal(levels(var), c("Y", "N"))) + } else { + browser() + } + return(res) +} + +# flags +T_flag <- function(x, ...) { + flag_names <- list(...) + + unknown_flags <- setdiff( + flag_names, + c( # common flags + "optional", "zero_or_more", "as_array", "named", "ignore", + # domain-specific flags + "subject_level_dataset_name", "subjid_var" + ) + ) + if (length(unknown_flags)) browser() + + flag_values <- as.list(rep(TRUE, length(flag_names))) + flags <- stats::setNames(flag_values, flag_names) + return(do.call(structure, append(list(x), flags))) +} + +T_map_to <- function(orig, dest) structure(orig, map_to = dest) # maps dataset col to a type the module understands + +# Pair documentation with module API ---- + +T_get_type_as_text <- function(elem) { + res <- "" + + types <- list( + group = "list", + logical = "logical", + factor = "factor", + integer = "integer", + cdisc_study_day = "integer", + numeric = "numeric", + mod = "character", + dataset_name = "character", + col = "character", + color = "character", + character = "character", + date = "Date", + datetime = "POSIXt", + YN = '"Y"/"N"' + ) + + if (elem$kind == "or") { + res <- paste(Map(T_get_type_as_text, elem$options), collapse = "|") + } else if (!(elem$kind %in% names(types))) { + message(paste("Missing kind", elem$kind)) + } else { + res <- types[[elem$kind]] + } + + return(res) +} + +T_get_use_as_text_lines <- function(elem) { + res <- character(0) + + if (elem$kind == "mod") { + res <- "Unique Shiny module identifier" + } else if (elem$kind == "dataset_name") { + if (isTRUE(attr(elem, "subject_level_dataset_name"))) { + res <- "Subject-level dataset name" + } else { + res <- "Dataset name" + } + } else if (elem$kind == "col") { + if (isTRUE(attr(elem, "subjid_var"))) { + res <- "Unique subject identifier column" + } else { + res <- sprintf("Indexes into dataset `%s`", elem$dataset_name) + if (!identical(elem$sub_kind, T_anything())) { + res <- c(res, sprintf("Expects `[%s]` values", T_get_type_as_text(elem$sub_kind))) + } + } + } else if (elem$kind == "cdisc_study_day") { + res <- "Represents a CDISC (non-zero) Study Day" + } else if (elem$kind == "color") { + res <- "Contains either an HTML (#xxxxxx) or an R color" + } else if (elem$kind %in% c("integer", "character", "group")) { + # nothing + } else { + message(paste("Missing use for kind", elem$kind)) + } + + return(res) +} + +T_attach_docs <- function(api, docs) { + stopifnot(is.character(docs[[1]])) + + attr(api, "docs") <- list( + type = T_get_type_as_text(api), + auto_desc = T_get_use_as_text_lines(api), + manual_desc = docs[[1]] + ) + + if (api$kind == "group") { + docs[[1]] <- NULL + + if (length(api$elements) != length(docs)) { + stop(sprintf("api and docs are of different lengths (%d and %d)", length(api), length(docs))) + } else if (!identical(names(api$elements), names(docs))) { + stop(sprintf( + "api and docs have different names (%s and %s)", + paste(names(api$elements), collapse = ","), paste(names(docs), collapse = ",") + )) + } + + for (name in names(api$elements)) { + api$elements[[name]] <- T_attach_docs(api$elements[[name]], docs[[name]]) + } + } + + return(api) +} + +T_eval_args <- function(args, eval_env) { + # evaluate arguments before handing them down to arg-rewriting routines + arg_names <- names(args) + for (i_arg in seq_along(args)) { + name <- arg_names[[i_arg]] + eval_res <- eval(args[[i_arg]], envir = eval_env) + args[i_arg] <- stats::setNames(list(eval_res), name) # R inferno 8.1.55 + } + return(args) +} + +# Permit caller to provide lists when arrays are desired by the module ---- + +T_honor_as_array_flag_inner <- function(api_field, elem) { + if (isTRUE(attr(api_field, "zero_or_more"))) { + attr(api_field, "zero_or_more") <- FALSE + for (i in seq_along(elem)) { + elem[[i]] <- T_honor_as_array_flag_inner(api_field, elem[[i]]) + } + } else if (api_field$kind == "group") { + elem_names <- names(elem) + for (i in seq_along(elem)) { + name <- elem_names[[i]] + if (!is.null(name) && name %in% names(api_field[["elements"]]) && !is.null(elem[[i]])) { + elem[i] <- stats::setNames( + list(T_honor_as_array_flag_inner(api_field[["elements"]][[name]], elem[[i]])), name + ) # R inferno 8.1.55 + } + } + } + + if (isTRUE(attr(api_field, "as_array")) && is.list(elem)) { + elem <- unlist(elem) + } + + return(elem) +} + +T_honor_as_array_flag <- function(mod_API, args) { + env_that_called_the_module_function <- parent.frame(2) + args <- T_eval_args(args, eval_env = env_that_called_the_module_function) + args <- T_honor_as_array_flag_inner(mod_API, args) + return(args) +} + +# Map allowed types to those expected by the module ---- + +T_honor_map_to_flag_inner <- function(datasets, api_field, elem, field_to_dataset_map, current_field_name) { + res <- list(map = field_to_dataset_map, actions = list()) + + if (isTRUE(attr(api_field, "zero_or_more"))) { + attr(api_field, "zero_or_more") <- FALSE + for (i in seq_along(elem)) { + res <- T_honor_map_to_flag_inner(datasets, api_field, elem[[i]], field_to_dataset_map, current_field_name) + } + } else if (api_field$kind == "group") { + group_field_to_dataset_map <- field_to_dataset_map # push new mapping used only inside group + + elem_names <- names(elem) + for (i in seq_along(elem)) { + name <- elem_names[[i]] + if (!is.null(name) && name %in% names(api_field[["elements"]]) && !is.null(elem[[i]])) { + subres <- T_honor_map_to_flag_inner( + datasets, api_field[["elements"]][[name]], elem[[i]], group_field_to_dataset_map, name + ) + res[["actions"]] <- append(res[["actions"]], subres[["actions"]]) + group_field_to_dataset_map <- subres[["map"]] # carry mappings defined inside this group + } + } + + res[["map"]] <- field_to_dataset_map # pop old mapping + } else if (api_field$kind == "dataset_name") { + res[["map"]][[current_field_name]] <- elem + } else if (api_field$kind == "col") { + map_to <- attr(api_field$sub_kind, "map_to") + if (!is.null(map_to)) { + dataset <- field_to_dataset_map[[api_field$dataset_name]] + if (is.null(dataset)) stop("Column refers to unknown dataset") # TODO: Check this upstream, warn earlier + res[["actions"]][[length(res[["actions"]]) + 1]] <- list(dataset = dataset, col = elem, kind = map_to) + } + } + + return(res) +} + +T_do_map <- function(datasets, action) { + dataset <- action[["dataset"]] + col <- action[["col"]] + kind <- action[["kind"]] + + col_data <- datasets[[dataset]][[col]] + if (!T_is_of_kind(col_data, kind)) { + mapped_from <- attr(col_data, "mapped_from") + if (!is.null(mapped_from)) { + stop(sprintf( + "Dataset %s column %s has already been mapped from %s to %s", + dataset, col, mapped_from, T_get_type_as_text(kind) + )) + } + + mapped_from <- class(col_data) + + attrs <- attributes(col_data) + if (kind == "logical" && T_is_of_kind(col_data, T_YN())) { + col_data <- (col_data == "Y") + } else { + kind_s <- T_get_type_as_text(kind) + stop(sprintf("Can't map data from type %s to %s", paste(mapped_from, collapse = ", "), kind_s)) + } + + attributes(col_data) <- attrs + attr(col_data, "mapped_from") <- mapped_from + } + + return(col_data) +} + +T_honor_map_to_flag <- function(datasets, mod_API, args) { + # NOTE: Here we overwrite affected dataset columns with the desired type for the purpose of + # a particular argument. A 'Y/N' field will be cast to `logical` an thus will become + # unavailable as a character variable. + # Ideally we would like to cast dataset columns to separate columns with a different + # name and overwrite args to point to those new columns, which would sidestep that + # restriction. This, however, would entail modifying the argument list in reactive + # time depending on the contents of the dataset, which would force mod_*_server to + # treat column name arguments as reactives. That seems too much of a hassle for little + # benefit. + env_that_called_the_module_function <- parent.frame(2) + args <- T_eval_args(args, eval_env = env_that_called_the_module_function) + + mapping_actions <- T_honor_map_to_flag_inner(datasets, mod_API, args, + field_to_dataset_map = list(), + current_field_name = "" + )[["actions"]] + + for (action in mapping_actions) { + dataset <- action[["dataset"]] + col <- action[["col"]] + datasets[[dataset]][[col]] <- T_do_map(datasets, action) + } + + return(datasets) +} + +inline_shiny_input <- function(elem, label = NULL, name_selector = NULL, label_elem = NULL) { + if (is.character(label) && length(label) == 1 && nchar(label) > 0) { + label_elem <- shiny::tags$label(`for` = NULL, label) + } + + res <- shiny::tags[["div"]]( + style = "display: flex; align-items: baseline; place-content: space-between; column-gap:1rem", + label_elem, name_selector, elem + ) + return(res) +} + +enable_nicer_unnamed_multicolumn_selection <- TRUE + +color_picker_input <- function(inputId, value = NULL) { + # https://developer.mozilla.org/en-US/docs/Web/HTML/Element/input/color + + # https://shiny.posit.co/r/articles/build/building-inputs/ + + # https://forum.posit.co/t/bookmarking-custom-inputs/162483 + + restored_value <- shiny::restoreInput(id = inputId, default = NULL) + if (!is.null(restored_value)) value <- restored_value + + list( + shiny::singleton(shiny::tags$head( + shiny::tags$script(r"--( + var color_picker_binding = new Shiny.InputBinding(); + $.extend(color_picker_binding, { + find: function(scope) { return scope.querySelectorAll('.color-picker'); }, + getValue: function(el) { return el.value; }, + subscribe: function(el, callback) { + $(el).on('change.color_picker_binding', function(e) { callback(); }); + }, + unsubscribe: function(el) { $(el).off('.color_picker_binding'); } + }); + Shiny.inputBindings.register(color_picker_binding); + )--") + )), + shiny::tags$input( + id = inputId, class = "color-picker", type = "color", style = "border:none", value = value + ) + ) +} + +# Module explorer app ---- +explorer_ui <- function() { + panel <- function(...) { + shiny::div( + class = "panel panel-default", + style = "background-color:#eff7ff;", + shiny::div(class = "panel-body", style = "padding-bottom:0.5rem;", ...) + ) + } + + ui <- shiny::fluidPage( + fontawesome::fa_html_dependency(), + shiny::tags$head(shiny::HTML("Davinci's Module Dressing Room")), + + # shamelessly stolen from https://github.com/insightsengineering/teal.modules.bsafe/blob/main/inst/www/bsafe.css + # and https://github.com/insightsengineering/teal.modules.bsafe/blob/main/R/mod_bsafe.R + shiny::tags$head(shiny::tags$style(shiny::HTML(r"--( + .toggle-label .chevron:before { + font-size: 2rem; + display: inline-block; + margin-left: 1rem; + content:"\203A"; + } + + .toggle-checkbox:checked + .toggle-label .chevron:before { + font-size: 2rem; + display: inline-block; + content:"\203A"; + transform: rotate(90deg); + } + + .margin_bottom_0px { margin-bottom:0px; } /* Gen-X CSS */ + + .inc_dec_button {background-color:#ffffffaa; border-radius:4px; border: 1px solid #000000aa; margin-bottom:14px;} + .inc_dec_button:hover {background-color:#eeeeeeaa; border: 1px solid #000000ff} + )--"))), + shiny::div(style = "height:1.5rem"), + shiny::sidebarLayout( + shiny::div( + class = "col-sm-3", + panel( + shiny::h4("DaVinci's Module Dressing Room", align = "center", + style = "margin-top:0; margin-bottom:2rem; font-weight:bold"), + inline_shiny_input( + shiny::selectInput( + inputId = "spec", label = NULL, + choices = names(module_specifications), selected = NULL, + selectize = FALSE + ), + label_elem = shiny::tags$label(`for` = "spec", "Module", title = "Module to configure") + ), + shiny::uiOutput("data_input") + ), + panel( + shiny::uiOutput("selectors") + ), + ), + shiny::mainPanel( + width = 9, style = "padding-left:0.5rem;", + panel( + shiny::conditionalPanel( + condition = "input.edit_code == false", + shiny::uiOutput("code") + ), + shiny::conditionalPanel( + condition = "input.edit_code == true", + shiny::tags$textarea( + id = "manual_code", + style = "width:100%; resize:vertical; height: 300px; font-family: 'Courier New', Courier, monospace;", + class = "form-control" + ) + ), + shiny::checkboxInput("edit_code", "Edit code", value = FALSE) + ), + shiny::uiOutput("module") + ) + ) + ) + + return(ui) +} + +message_well <- function(title, contents, color = "f5f5f5") { + style <- sprintf(r"---( + padding: 0.5rem; + padding-left: 1rem; + margin-bottom: 20px; + background-color: %s; + border: 1px solid #e3e3e3; + border-radius: 4px; + -webkit-box-shadow: inset 0 1px 1px rgba(0,0,0,.05); + box-shadow: inset 0 1px 1px rgba(0,0,0,.05); + )---", color) + + res <- list(shiny::h3(title)) + if (length(contents)) res <- append(res, list(shiny::tags[["div"]](contents, style = style))) + return(res) +} + +explorer_server_with_datasets <- function(caller_datasets = NULL) { + explorer_server <- function(input, output, session) { + shiny::observe({ + input <- shiny::reactiveValuesToList(input) + if ("module_id" %in% names(input)) { # FIXME: Should not depend on specific input + session$doBookmark() + } + }) + shiny::onBookmarked(shiny::updateQueryString) + + datasets <- shiny::reactive({ + res <- caller_datasets + if (is.null(res)) { + dataset_info <- input[["datasets"]] + shiny::req(dataset_info) + res <- list() + for (i_row in seq_len(nrow(dataset_info))) { + row <- dataset_info[i_row, ] + res[[row[["name"]]]] <- readRDS(row[["datapath"]]) + } + } + return(res) + }) + + well <- function(title_ui, contents, expanded, checkbox_id = NULL) { + style <- r"---( + min-height: 20px; + padding: 19px; + padding-top: 14px; + padding-bottom: 0px; + padding-right: 10px; + margin-bottom: 20px; + background-color: #1155a00c; + border: 1px solid #00000020; + border-radius: 4px; + )---" + + checked <- if (isFALSE(expanded)) NULL else NA # awkward mapping, but HTML is what it is + + res <- list( + shiny::div( + title_ui, + shiny::tags$input( + id = checkbox_id, type = "checkbox", class = "toggle-checkbox", + checked = checked, style = "display: none;" + ), + shiny::tags$label( + `for` = checkbox_id, class = "toggle-label", + shiny::tags$span(class = "chevron") + ), + style = "display:flex; align-items:baseline;" + ) + ) + + if (length(contents)) { + res <- append( + res, + list(shiny::div( + shiny::conditionalPanel( + condition = paste0("input['", checkbox_id, "']"), + shiny::tags[["div"]](contents, style = style) + ) + )) + ) + } + + return(res) + } + + column_selector <- function(elem, datasets, visible_datasets, inputs, id, multiple) { + dataset_name <- elem[["dataset_name"]] + dataset_slot <- mget(dataset_name, envir = visible_datasets, ifnotfound = list(NULL), inherits = TRUE)[[1]] + + choices <- c() + if (!is.null(dataset_slot)) { + dataset <- datasets[[dataset_slot]] + for (col_name in names(dataset)) { + if (T_is_of_kind(dataset[[col_name]], elem[["sub_kind"]])) { + label <- attr(dataset[[col_name]], "label") + if (is.null(label)) { + choices <- c(choices, col_name) + } else { + choices[[paste0(col_name, " [", label, "]")]] <- col_name + } + } + } + } + + if (length(choices) == 0) choices <- inputs[[id]] + + # FIXME : Use another selector because selectInput does not preserve the order of columns + # on bookmark restoration (see https://github.com/rstudio/shiny/issues/1490, + # which predates trump's presidency) + ui <- shiny::selectInput( + inputId = id, label = NULL, + choices = choices, selected = inputs[[id]], + selectize = multiple, multiple = multiple + ) + + return(ui) + } + + compute_ui_info_inner <- function(visible_datasets, label, name, elem, inputs, datasets, counts) { + if (isTRUE(attr(elem, "ignore"))) { + # NOTE: This element should have been filtered out at this point + return(list( + ui = shiny::p(paste("**FIXME: should have been ignored**", name)), + input_ids = NULL, dependencies = list() + )) + } + + ui <- list() + input_ids <- NULL + deps <- list() + + if (elem[["kind"]] == "mod") { + ui <- shiny::textInput( + inputId = name, label = NULL, value = inputs[[name]], + placeholder = "" + ) + input_ids <- name + } else if (elem[["kind"]] == "dataset_name") { + ui <- shiny::selectInput( + inputId = name, label = NULL, + choices = names(datasets), selected = inputs[[name]], + selectize = FALSE + ) + + if (!is.null(inputs[[name]]) && !is.null(label)) { + visible_datasets[[label]] <- inputs[[name]] + } + input_ids <- name + deps[[length(deps) + 1]] <- name # columns depend on datasets, so we ask for another pass + } else if (elem[["kind"]] == "col") { + ui <- column_selector(elem, datasets, visible_datasets, inputs, name, multiple = FALSE) + input_ids <- name + } else if (elem[["kind"]] == "integer" || elem[["kind"]] == "cdisc_study_day") { + possible_values <- c(inputs[[name]], elem[["min"]], elem[["max"]], 0) + value <- possible_values[which(is.finite(possible_values))[1]] + + ui <- shiny::numericInput( + inputId = name, label = NULL, value = value, + min = elem[["min"]], max = elem[["max"]], width = "5em" + ) + input_ids <- name + } else if (elem[["kind"]] == "color") { + ui <- color_picker_input(inputId = name, value = inputs[[name]]) + input_ids <- name + } else if (elem[["kind"]] == "group") { + child_visible_datasets <- new.env(parent = visible_datasets) + + input_ids <- list() + for (child_param in seq_along(elem$elements)) { + child_name <- names(elem$elements)[[child_param]] + child_elem <- elem[["elements"]][[child_param]] + + child_info <- compute_ui_info_outer( + child_visible_datasets, + label = child_name, + name = paste(c(name, child_name), collapse = "-"), + child_elem, inputs, datasets, counts + ) + + ui[[length(ui) + 1]] <- child_info[["ui"]] + input_ids[[child_name]] <- child_info[["input_ids"]] + deps <- append(deps, child_info[["dependencies"]]) + } + } else { + ui <- shiny::p(paste("TODO: ", elem[["kind"]])) + input_ids <- list() + } + + attr(input_ids, "as_array") <- attr(elem, "as_array") + + return(list(ui = ui, input_ids = input_ids, dependencies = deps)) + } + + # We use -/+ buttons instead of a shiny::numericInput because that clicking that selector twice in + # quick succession triggers a race condition in the context of renderUIs that redraw the selector itself + # Thus, we avoid representing the absolute number of elements and instead only capture the purpose of + # incrementing or decrementing whatever value is stored on the server + button_delta_id <- "button_delta" + inc_dec_buttons <- function(id) { + list( + shiny::tags[["button"]]( + shiny::icon("minus"), class = "inc_dec_button", + onclick = sprintf( + "Shiny.setInputValue('%s', {id:'%s', delta:-1}, {priority:'event'});", button_delta_id, id + ) + ), + shiny::tags[["button"]]( + shiny::icon("plus"), class = "inc_dec_button", + onclick = sprintf( + "Shiny.setInputValue('%s', {id:'%s', delta:+1}, {priority:'event'});", button_delta_id, id + ) + ) + ) + } + + # Bookmark shenanigans ---- + counts_rv <- shiny::reactiveValues() + candidate_state <- NULL + + shiny::onBookmark(function(state) { + state$values$counts <- shiny::reactiveValuesToList(counts_rv) + }) + + shiny::onRestored(function(state) { + candidate_state <<- state$input + counts <- state$values$counts + for (name in names(counts)) counts_rv[[name]] <- counts[[name]] + + if (isTRUE(state$input[["edit_code"]])) { + shiny::updateTextAreaInput( + session = session, "manual_code", + value = state$input[["manual_code"]] + ) + } + }) + + retrigger_rv <- shiny::reactiveVal(0) + shiny::observe({ + msg <- input[[button_delta_id]] + if (!is.null(msg)) { + id <- msg[["id"]] + v <- shiny::isolate(counts_rv[[id]]) + new_v <- max(0, v + msg[["delta"]]) + counts_rv[[id]] <- new_v + if (!identical(v, new_v)) retrigger_rv(shiny::isolate(retrigger_rv() + 1)) + } + }) + + compute_ui_info_outer <- function(visible_datasets, label, name, elem, inputs, datasets, counts) { + if (isTRUE(attr(elem, "ignore"))) { + return(list(ui = NULL, input_ids = NULL, dependencies = NULL)) + } # NOTE: early out + + res <- NULL + + docs <- attr(elem, "docs") + doc_pieces <- paste0("[", docs[["type"]], "]") + if (nchar(docs[["manual_desc"]]) > 0) doc_pieces <- c(doc_pieces, docs[["manual_desc"]]) + if (length(docs[["auto_desc"]])) doc_pieces <- c(doc_pieces, paste(docs[["auto_desc"]], collapse = "\n")) + + hover_info <- paste(doc_pieces, collapse = "\n") + + dependencies <- list() + + optional_ui <- NULL + if (isTRUE(attr(elem, "optional"))) { + checkbox_id <- paste(c(name, "enabled"), collapse = "-") + expanded <- isTRUE(inputs[[checkbox_id]]) + checked <- if (isFALSE(expanded)) NULL else NA # awkward mapping, but HTML is what it is + checkbox <- list(shiny::tags$input( + id = checkbox_id, type = "checkbox", class = "optional-checkbox", + checked = checked, style = "margin-right:0.5rem;" + )) + + dependencies <- c(dependencies, checkbox_id) + if (expanded) { + optional_ui <- checkbox + } else { + ui <- list(shiny::div(checkbox, + shiny::tags$label( + `for` = checkbox_id, label, + style = "font-weight:normal;font-style:italic;margin-bottom:0px", + title = hover_info + ), + style = "display:flex;align-items:baseline;padding-bottom:1rem;" + )) + + return(list(ui = ui, input_ids = NULL, dependencies = dependencies)) # NOTE: early out + } + } + + named <- isTRUE(attr(elem, "named")) + zero_or_more <- isTRUE(attr(elem, "zero_or_more")) + + if (enable_nicer_unnamed_multicolumn_selection && zero_or_more && !named && elem$kind == "col") { + # NOTE: special-case with a multiselector for a more streamlined interface + ui <- column_selector(elem, datasets, visible_datasets, inputs, name, multiple = TRUE) + input_ids <- name + + ui$attribs$class <- paste(ui$attribs$class, "margin_bottom_0px") + + # Hacky alignment of selectInput + label_elem <- list(shiny::tags$span(optional_ui, + shiny::tags$label(`for` = NULL, label, title = hover_info), + style = "display:inline-flex; align-items:baseline; padding-top:0.7rem;" + )) + + ui <- shiny::tags[["div"]]( + style = "display: flex; align-items: flex-start; place-content: space-between; column-gap:1rem", + label_elem, ui + ) + + res <- list(ui = ui, input_ids = input_ids, dependencies = dependencies) + } else if (zero_or_more) { + attr(elem, "zero_or_more") <- FALSE + + input_ids <- list() + + possible_values <- c(counts[[name]], 0) + count <- possible_values[which(is.finite(possible_values))[1]] + + counts_rv[[name]] <- ifelse(name %in% names(counts), counts[[name]], 0) + + sub_ui <- list() + + name_input_ids <- character(0) + for (i_rep in seq_len(count)) { + child_name <- paste0(name, "-", i_rep) + + name_selector <- NULL + + if (named) { + name_sel_id <- paste0(child_name, "-name") + name_input_ids <- c(name_input_ids, name_sel_id) + name_selector <- shiny::textInput( + inputId = name_sel_id, label = NULL, + value = inputs[[name_sel_id]], placeholder = "" + ) + } + + child_info <- compute_ui_info_inner(visible_datasets, + label = NULL, child_name, elem, + inputs, datasets, counts + ) + child_ui <- child_info[["ui"]] + + if (elem$kind == "group") { # repeats #eenahw partially; not ready to compress it yet + child_ui <- list(well( + title_ui = name_selector, child_ui, + expanded = inputs[[child_name]], + checkbox_id = child_name + )) + } else { + child_ui <- list(inline_shiny_input(child_ui, label = NULL, name_selector = name_selector)) + } + + sub_ui <- append(sub_ui, child_ui) + input_ids <- append(input_ids, list(child_info[["input_ids"]])) + dependencies <- append(dependencies, child_info[["dependencies"]]) + } + sub_ui <- append(sub_ui, inc_dec_buttons(name)) + + title_ui <- list(optional_ui, shiny::tags$label(`for` = name, class = "chevron", label, title = hover_info)) + ui <- list(well(title_ui, sub_ui, expanded = inputs[[name]], name)) + + if (named) { + attr(input_ids, "name_input_ids") <- name_input_ids + } + + attr(input_ids, "as_array") <- attr(elem, "as_array") + + res <- list(ui = ui, input_ids = input_ids, dependencies = dependencies) + } else { + res <- compute_ui_info_inner(visible_datasets, label, name, elem, inputs, datasets, counts) + res[["dependencies"]] <- c(dependencies, res[["dependencies"]]) + + if (elem$kind == "group") { # repeats #eenahw partially; not ready to compress it yet + title_ui <- list(optional_ui, shiny::tags$label(`for` = name, class = "chevron", label, title = hover_info)) + res[["ui"]] <- list(well(title_ui, res[["ui"]], + expanded = inputs[[name]], + checkbox_id = name + )) + } else { + if (!is.null(optional_ui)) { + res[["ui"]] <- list(inline_shiny_input( + res[["ui"]], + label_elem = list(shiny::tags$span(optional_ui, + shiny::tags$label(`for` = NULL, label, title = hover_info), + style = "display:inline-flex; align-items:baseline;" + )) + )) + } else { + res[["ui"]] <- list( + shiny::tags[["div"]](style = "display: flex; align-items: baseline; place-content: space-between; column-gap:1rem", + shiny::div(shiny::tags$label(`for` = NULL, label), style = "display:inline-flex;", title = hover_info), res[["ui"]] + ) + ) + } + } + } + + return(res) + } + + ui_and_ids <- shiny::reactive({ + ui <- list() + input_ids <- list() + deps <- list() + + selected_spec <- input[["spec"]] + shiny::req(selected_spec) + datasets <- datasets() + + inputs <- shiny::isolate(shiny::reactiveValuesToList(input)) + if (!is.null(candidate_state)) { + inputs <- candidate_state + candidate_state <<- NULL + } + + visible_datasets <- new.env(parent = emptyenv()) + spec_elements <- module_specifications[[selected_spec]] + + counts <- shiny::isolate(shiny::reactiveValuesToList(counts_rv)) + info <- shiny::maskReactiveContext( + compute_ui_info_inner(visible_datasets, "placeholder_label", name = NULL, spec_elements, inputs, datasets, counts) + ) + ui <- info[["ui"]] + input_ids <- info[["input_ids"]] + deps <- info[["dependencies"]] + + for (dep in deps) input[[dep]] # makes this reactive depend only on certain inputs + retrigger_rv() + + return(list(ui = ui, input_ids = input_ids)) + }) + + output[["selectors"]] <- shiny::renderUI(ui_and_ids()[["ui"]]) + + output[["data_input"]] <- shiny::renderUI({ + ui <- NULL + if (is.null(caller_datasets)) { + # no caller datasets: ask the user for some + ui <- shiny::tagList( + # Hacky alignment of fileInput + shiny::tags[["div"]]( + style = "display: flex; align-items: flex-start; place-content: space-between; column-gap:1rem", + shiny::tags$label( + `for` = "datasets", "Datasets", style = "padding-top: 0.7rem;", + title = "Input datasets for selected module" + ), + shiny::fileInput( + inputId = "datasets", label = NULL, multiple = TRUE, accept = ".rds", + capture = NULL + ) + ) + ) + } else { + ui <- shiny::HTML(sprintf("Preloaded datasets: %s", paste(names(caller_datasets), collapse = ", "))) + } + + return(ui) + }) + + indent <- function(code, level) { + indent_string <- strrep(" ", max(0, level)) + return(paste0(indent_string, code)) + } + + resolve_rhs <- function(id, parent_indent_level) { + res <- "" + if (is.character(id) && length(id) == 1) { + param_value <- input[[id]] + res <- deparse1(param_value) + } else if (is.list(id)) { + subres <- c() + + elem_names <- local({ + res <- names(id) + name_input_ids <- attr(id, "name_input_ids") + if (length(name_input_ids) > 0) { + res <- Map(function(id) { + s <- input[[id]] + if (identical(s, "")) { + s <- NULL + } else { + s <- deparse(s) + } + }, name_input_ids) + } + return(res) + }) + + for (i_elem in seq_along(id)) { + name <- NULL + if (i_elem <= length(elem_names)) name <- elem_names[[i_elem]] + if (identical(name, "")) name <- NULL + subres <- c( + subres, + paste(c(name, resolve_rhs(id[[i_elem]], parent_indent_level + 1)), collapse = " = ") + ) + } + + as_array <- isTRUE(attr(id, "as_array")) + container <- ifelse(as_array, "c", "list") + + res <- "" + if (length(subres)) { + res <- paste0( + container, + "(\n", + paste(subres |> indent(parent_indent_level + 1), collapse = ",\n"), + "\n", + ")" |> indent(parent_indent_level) + ) + } else { + res <- paste0(res, container, "()") + } + } else { + res <- "TODO" + } + return(res) + } + + code <- shiny::reactive({ + selected_spec <- input[["spec"]] + t <- paste0(selected_spec, "(\n") + + params <- local({ + res <- c() + ids <- ui_and_ids()[["input_ids"]] + for (i_val in seq_along(ids)) { + param_name <- names(ids)[[i_val]] + id <- ids[[i_val]] + res <- c( + res, + paste(c(param_name, resolve_rhs(id, parent_indent_level = 1)), collapse = " = ") |> indent(1) + ) + } + return(res) + }) + + t <- paste0(t, paste(params, collapse = ",\n")) + t <- paste0(t, "\n)") + + # NOTE(miguel): If you want to plug your own styler, here would be a good place to do so. Here's an (ugly) example: + # t <- sapply(parse(text = t), function(s) deparse1(s, collapse = '\n', width.cutoff = 80L)) # nolint + + return(t) + }) + + code_highlight_differences <- function(a, b) { + # FIXME(miguel): Not the correct place to do this operation. We could have the parse tree prior to rendering it as + # text, so a tree comparison would be less heuristic. That would involve building a nested list + # inside code()+resolve_rhs, which we would also use here. Producing the indented code from that + # nested list would also be cleaner than the ad-hoc formatting I do in the `code()` reactive, but... + # NOTE(miguel): we're in a hurry, so look ma, no hands: + + drop_trailing_comma <- function(strings) { + return(substr(strings, 1, nchar(strings) - endsWith(strings, ","))) + } + + as <- strsplit(a, "\n", fixed = TRUE)[[1]] |> drop_trailing_comma() + bs <- strsplit(b, "\n", fixed = TRUE)[[1]] + res <- character(0) + for (e in bs) { + indices <- which(drop_trailing_comma(e) == as) + if (length(indices)) { + as <- as[-indices[[1]]] + } else { + e <- paste0("", e, "") + } + res <- c(res, e) + } + return(paste(res, collapse = "\n")) + } + + prev_code_update_delay_s <- 3 # TODO: constant + prev_code <- prev_diffed_code <- "" + prev_code_t <- Sys.time() + + output[["code"]] <- shiny::renderUI({ # TODO: Add 'copy' icon, like the ones on code snippets on vignettes + code <- code() + + code <- gsub("&", "&", code, fixed = TRUE, useBytes = TRUE) + code <- gsub("<", "<", code, fixed = TRUE, useBytes = TRUE) + code <- gsub(">", ">", code, fixed = TRUE, useBytes = TRUE) + + t_current <- Sys.time() + t_diff <- as.numeric(difftime(t_current, prev_code_t, units = "secs")) + if (prev_code_update_delay_s <= t_diff) prev_diffed_code <<- prev_code + prev_code <<- code + prev_code_t <<- t_current + + code_to_print <- code + if (!identical(prev_diffed_code, code)) code_to_print <- code_highlight_differences(prev_diffed_code, code) + + res <- shiny::HTML(paste0( + "
",
+        code_to_print,
+        "
" + )) + + return(res) + }) + + shiny::observeEvent(input[["edit_code"]], { + if (isTRUE(input[["edit_code"]])) { + shiny::updateTextAreaInput(session = session, "manual_code", value = code()) + } + }) + + output[["module"]] <- shiny::renderUI({ + code_to_eval <- NULL + if (isTRUE(input[["edit_code"]])) { + code_to_eval <- input[["manual_code"]] + shiny::req(is.character(code_to_eval)) + } else { + code_to_eval <- trimws(code()) + } + + get_package_maintainer_name <- function() { + desc <- utils::packageDescription("dv.papo")[["Maintainer"]] + if (is.character(desc) && length(desc) == 1 && nchar(desc) > 0) { + desc <- paste0("`", desc, "`") + } else { + # NOTE: Available after installing from source, but not under devtools + desc <- "the package maintainer" + } + return(desc) + } + + error_and_ui <- local({ + ui <- NULL + + spec <- input[["spec"]] + + build_error <- function(title, condition, preface) { + return(list(error = list(title = title, condition = condition, preface = preface))) + } + + if (!is.character(spec) || nchar(input[["spec"]]) == 0) { + return(build_error( + title = "Module selection error", + condition = base::simpleError("No DaVINCI module selected on the `Module` drop-down."), + preface = "Module selection error" + )) # FIXME: repeats message + } + + if (!startsWith(code_to_eval, spec)) { + return(build_error( + title = "Module configuration error", + condition = base::simpleError(paste("Expected call to", spec)), + preface = "Module configuration error" + )) # FIXME: repeats message + } + + # FIXME(miguel): We should parse and evaluate arguments separately outside of a reactive environment + # to see if any of them is badly constructed, but here I take a shortcut and evaluate + # them all inside a list() + list_of_args <- paste0("list", substr(code_to_eval, nchar(input[["spec"]]) + 1, nchar(code_to_eval))) + parsed_code <- try(parse(text = list_of_args), silent = TRUE) + eval_result <- try(eval(parsed_code), silent = TRUE) + if (inherits(eval_result, "try-error")) { + attr(eval_result, "condition")[["call"]][[1]] <- parse(text = spec)[[1]] # undo the spec->`list` substitution + return(build_error( + title = "Syntax error", + condition = attr(eval_result, "condition"), + preface = "Cannot parse the code provided." + )) + } + + # NOTE(miguel): With that out of the way, this shouldn't fail but I keep it just in case + parsed_code <- try(parse(text = code_to_eval), silent = TRUE) + if (inherits(parsed_code, "try-error")) { + return(build_error( + title = "Syntax error", + condition = attr(parsed_code, "condition"), + preface = "Cannot parse the code provided." + )) + } + + ui_server_id <- try(eval(parsed_code), silent = TRUE) + shiny::req(!is.null(ui_server_id)) + if (inherits(ui_server_id, "try-error")) { + return(build_error( + title = "Module Development Error", + condition = attr(ui_server_id, "condition"), + preface = paste0( + "Please report the following error to ", + get_package_maintainer_name(), "." + ) + )) + } + + if (!setequal(c("ui", "server", "module_id"), names(ui_server_id))) { + return(build_error( + title = "Module Configuration Error", + condition = base::simpleError("The provided code does not return a {ui, server, module_id} triplet."), + preface = paste0("Are you actually calling ", input[["spec"]], "?") + )) + } + + id <- ui_server_id[["module_id"]] + if (is.function(ui_server_id[["ui"]])) ui <- ui_server_id[["ui"]](id) + + afmm <- list( + unfiltered_dataset = datasets, + filtered_dataset = datasets, + module_output = function() list() + ) + + server_return_val <- try(ui_server_id[["server"]](afmm), silent = TRUE) + if (inherits(server_return_val, "try-error")) { + return(build_error( + title = "Module Development Error", + condition = attr(server_return_val, "condition"), + preface = paste0( + "Please report the following error to ", + get_package_maintainer_name(), "." + ) + )) + } + + return(list(ui = ui)) + }) + + ui <- error_and_ui[["ui"]] + error <- error_and_ui[["error"]] + + if (!is.null(error)) { + error_message <- error$condition[["message"]] + error_context <- paste(deparse(error$condition[["call"]]), collapse = "\n") + + ui <- list( + message_well(error$title, error$preface, color = "#f4d7d7"), + shiny::p("Message is:"), + shiny::pre(error_message), + shiny::p("And happened in the vicinity of:"), + shiny::pre(error_context) + ) + } + + return(ui) + }) + + NULL + } + + return(explorer_server) +} + +#' Interactive demo/configuration tool for [mod_patient_profile()] +#' +#' Launch an interactive configuration app for [mod_patient_profile()]. This application guides the user through the +#' configuration of the module, offering an experimental point-and-click interface to the module API. Help is accessible +#' by hovering over any of the provided parameters. \cr +#' To try it using demo data, run `dv.papo::explorer_app(dv.papo:::prep_safety_data())` in your R prompt. +#' +#' @param datasets `[list(data.frame(n))]` (optional) Datasets available to the module. One of them should be a +#' demographic subject-level dataset and the rest should be visit-dependent datasets. If not provided, the UI offers a +#' file input selector that is functionally equivalent. +#' +#' @export +explorer_app <- function(datasets = NULL) { + shiny::shinyApp( + ui = explorer_ui, + server = explorer_server_with_datasets(caller_datasets = datasets), + enableBookmarking = "url" + ) +} + +app_creator_feedback_ui <- function(id) { + id <- paste(c(id, "validator"), collapse = "-") + ns <- shiny::NS(id) + return(shiny::uiOutput(ns("ui"))) +} + +app_creator_feedback_server <- function(id, warning_messages, error_messages, ui) { + id <- paste(c(id, "validator"), collapse = "-") + module <- shiny::moduleServer( + id, + function(input, output, session) { + output[["ui"]] <- shiny::renderUI({ + res <- list() + warn <- warning_messages() + if (length(warn)) { + res[[length(res) + 1]] <- message_well("Module configuration warnings", Map(shiny::p, warn), color = "#fff7ef") + } + + err <- error_messages() + if (length(err)) { + res[[length(res) + 1]] <- message_well("Module configuration errors", Map(shiny::p, err), color = "#f4d7d7") + } + + if (length(error_messages()) == 0) res <- append(res, list(ui)) + return(res) + }) + } + ) + + return(module) +} diff --git a/R/global_params.r b/R/global_params.r new file mode 100644 index 0000000..91dbc69 --- /dev/null +++ b/R/global_params.r @@ -0,0 +1,16 @@ +CONST <- poc( + width_of_patient_selector_in_columns = 4, + decode_max_width_before_wrap_in_characters = 15, + color_for_missing_analysis_indicator_levels = "darkgray", + default_palette = c( + `REFERENCE RANGE` = "#91eec2", + `Reference range` = "#91eec2", + `reference range` = "#91eec2", + `NORMAL` = "green4", `LOW` = "red3", `HIGH` = "red2", + `Normal` = "green4", `Low` = "red3", `High` = "red2", + `normal` = "green4", `low` = "red3", `high` = "red2", + `MILD` = "lightgreen", `MODERATE` = "gold1", `SEVERE` = "red", + `Mild` = "lightgreen", `Moderate` = "gold1", `Severe` = "red", + `mild` = "lightgreen", `moderate` = "gold1", `severe` = "red" + ) +) diff --git a/R/mock_patient_profile.R b/R/mock_patient_profile.R new file mode 100644 index 0000000..5ad8a22 --- /dev/null +++ b/R/mock_patient_profile.R @@ -0,0 +1,211 @@ +#' Mock UI for papo module +#' +#' @param id A unique identifier. +#' +#' @return Shiny UI for the papomodule. +#' +#' @keywords internal +#' +#' @export +#' +mock_patient_profile_UI <- function(request) { # nolint + ui <- shiny::fluidPage( + shiny::tags$h1("Patient profile", class = "mod-title"), + shiny::actionButton("jump", "Click to jump"), + mod_patient_profile_UI(id = "papo") + ) + return(ui) +} + + +#' Mock server for papo module +#' +#' Uses adsl, adae, and adcm data of roche dataset. +#' +#' @param input,output,session Internal parameters for shiny. +#' +#' @keywords internal +#' +#' @export +#' +mock_patient_profile_server <- function(input, output, session) { + data_list <- prep_safety_data() + + subject_level_dataset <- shiny::reactive(data_list[["adsl"]]) + extra_datasets <- shiny::reactive(data_list[setdiff(names(data_list), "adsl")]) + + # exclude all non-papo inputs from bookmarking + # plotly does not namespace its inputs, so this can't be done from inside the module + shiny::observe({ + all <- names(input) + papo_filter <- startsWith(all, "papo") + non_papo_inputs <- all[!papo_filter] + shiny::setBookmarkExclude(non_papo_inputs) + }) + + mod_patient_profile_server( + id = "papo", + subject_level_dataset = subject_level_dataset, + extra_datasets = extra_datasets, + subjid_var = "USUBJID", + sender_ids = list("test" = shiny::reactive({ # recreate sender_ids structure of Module Manager + list(subj_id = shiny::reactive({ + shiny::req(input$jump) + "01-701-1033" + })) + })), + summary = list( + vars = c( + "SITEID", + "AGE", + "SEX", + "RACE", + "ETHNIC", + "ARM", + "DCREASCD", + "TRT01A" + ), + column_count = 3 + ), + listings = list( + "Adverse Event" = list(dataset = "adae", default_vars = NULL), + "Concomitant Medication" = list(dataset = "cm", default_vars = NULL) + ), + plots = list( + timeline_info = c( + trt_start_date = "TRTSDT", + trt_end_date = "TRTEDT", + icf_date = "RFICDT", + part_end_date = "RFENDT" + ), + vline_vars = list( + "Informed Consent Day" = "RFICDT", + "Study Treatment Stop Day" = "TRTEDT" + ), + vline_day_numbers = c( + "Study Treatment Start Day : Day 1" = 1, + "Test" = 50, + "Test2" = 75, + "Test3" = 100 + ), + range_plots = list( + "Adverse Events Plot" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", + end_date = "AENDT", + decode = "AEDECOD", + grading = "AESEV", + serious_ae = "AESER" + ), + tooltip = c( + "AE Term: " = "AEDECOD", + "AE Reported Term: " = "AETERM", + "Primary SOC: " = "AESOC", + "Intensity: " = "AESEV", + "Serious Event: " = "AESER", + "AE Start Date: " = "ASTDT", + "AE Stop Date: " = "AENDT", + "AE Start Day: " = "ASTDY", + "AE Stop Day: " = "AENDY" + ) + ), + "Concomitant Medication Plot" = list( + dataset = "cm", + vars = c( + start_date = "CMSTDT", + end_date = "CMENDT", + decode = "CMDECOD", + grading = "CMINDC" + ), + tooltip = c( + "Standardized Medication Name: " = "CMDECOD", + "Indication: " = "CMINDC", + "CM Dose: " = "CMDOSE", + "CM Dose Unit: " = "CMDOSU", + "CM START Date: " = "CMSTDTC", + "CM End Date: " = "CMENDTC", + "CM START Day: " = "CMSTDY", + "CM END Day: " = "CMENDY" + ) + ) + ), + value_plots = list( + "Lab plot" = list( + dataset = "lb", + vars = c( + analysis_param = "PARAM", + analysis_val = "AVAL", + analysis_date = "ADT", + analysis_indicator = "ANRIND", + range_low_limit = "A1LO", + range_high_limit = "A1HI" + ), + tooltip = c( + "Lab Parameter: " = "PARAM", + "Lab Test Date: " = "ADT", + "Lab Test Visit :" = "AVISIT", + "
High Limit: " = "A1HI", + "Lab Standard Value: " = "AVAL", + "Lower Limit: " = "A1LO", + "
Analysis Indicator: " = "ANRIND" + ) + ), + "Vital Sign Plot" = list( + dataset = "vs", + vars = c( + analysis_param = "PARAM", + analysis_val = "AVAL", + analysis_date = "ADT", + analysis_indicator = "VISIT", + range_low_limit = NULL, + range_high_limit = NULL, + summary_stats = "AVAL_MEAN" + ), + tooltip = c( + "Vital sign Parameter: " = "PARAM", + "Vital sign Date: " = "ADT", + "Vital sign Visit: " = "AVISIT", + "
Vital sign Value: " = "AVAL", + "Vital sign mean value by visits: " = "AVAL_MEAN" + ) + ) + ) + ) + ) +} + + + +#' Run papo mock +#' +#' \code{mock_patient_profile_app()} runs the \pkg{dv.papo} module +#' with dummy data. +#' +#' @keywords internal +#' +#' @export +#' +mock_patient_profile_app <- function(auto_update_query_string = FALSE) { + server <- mock_patient_profile_server + enable_bookmarking <- "disable" + + if (auto_update_query_string) { + server <- function(input, output, session) { + shiny::observe({ + shiny::reactiveValuesToList(input) # Trigger this observer every time an input changes + session$doBookmark() + }) + shiny::onBookmarked(shiny::updateQueryString) + + return(mock_patient_profile_server(input, output, session)) + } + enable_bookmarking <- "url" + } + + shiny::shinyApp( + ui = mock_patient_profile_UI, + server = server, + enableBookmarking = enable_bookmarking + ) +} diff --git a/R/mock_with_mm.R b/R/mock_with_mm.R new file mode 100644 index 0000000..5d33d13 --- /dev/null +++ b/R/mock_with_mm.R @@ -0,0 +1,145 @@ +#' Run an example for Patient profile integrated in the module manager +#' +#' Launches an example app that shows a patient profile module integrated in the +#' module manager surface. Displays data from the \pkg{safetyData} package. +#' +#' @keywords internal +#' +#' @export +#' +mock_with_mm_app <- function() { + dataset_list <- list( + "demo" = prep_safety_data(5), + "demo2" = prep_safety_data(10) + ) + + module_list <- list( + "Papo" = mod_patient_profile( + module_id = "mock_app", + subjid_var = "USUBJID", + sender_ids = NULL, + subject_level_dataset_name = "adsl", + summary = list( + vars = c( + "SITEID", + "AGE", + "SEX", + "RACE", + "ETHNIC", + "ARM", + "DCREASCD", + "TRT01A" + ), + column_count = 3 + ), + listings = list( + "Adverse Event" = list(dataset = "adae", default_vars = NULL), + "Concomitant Medication" = list(dataset = "cm", default_vars = NULL) + ), + plots = list( + timeline_info = c( + trt_start_date = "TRTSDT", + trt_end_date = "TRTEDT", + icf_date = "RFICDT", + part_end_date = "RFENDT" + ), + vline_vars = c( + "Informed Consent Day" = "RFICDT", + "Study Treatment Stop Day" = "TRTEDT" + ), + vline_day_numbers = c( + "Study Treatment Start Day : Day 1" = 1 + ), + range_plots = list( + "Adverse Events Plot" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", + end_date = "AENDT", + decode = "AEDECOD", + grading = "AESEV", + serious_ae = "AESER" + ), + tooltip = c( + "AE Term: " = "AEDECOD", + "AE Reported Term: " = "AETERM", + "Primary SOC: " = "AESOC", + "Intensity: " = "AESEV", + "Serious Event: " = "AESER", + "AE Start Date: " = "ASTDT", + "AE Stop Date: " = "AENDT", + "AE Start Day: " = "ASTDY", + "AE Stop Day: " = "AENDY" + ) + ), + "Concomitant Medication Plot" = list( + dataset = "cm", + vars = c( + start_date = "CMSTDT", + end_date = "CMENDT", + decode = "CMDECOD", + grading = "CMINDC" + ), + tooltip = c( + "Standardized Medication Name: " = "CMDECOD", + "Indication: " = "CMINDC", + "CM Dose: " = "CMDOSE", + "CM Dose Unit: " = "CMDOSU", + "CM START Date: " = "CMSTDTC", + "CM End Date: " = "CMENDTC", + "CM START Day: " = "CMSTDY", + "CM END Day: " = "CMENDY" + ) + ) + ), + value_plots = list( + "Lab plot" = list( + dataset = "lb", + vars = c( + analysis_param = "PARAM", + analysis_val = "AVAL", + analysis_date = "ADT", + analysis_indicator = "ANRIND", + range_low_limit = "A1LO", + range_high_limit = "A1HI" + ), + tooltip = c( + "Lab Parameter: " = "PARAM", + "Lab Test Date: " = "ADT", + "Lab Test Visit :" = "AVISIT", + "
High Limit: " = "A1HI", + "Lab Standard Value: " = "AVAL", + "Lower Limit: " = "A1LO", + "
Analysis Indicator: " = "ANRIND" + ) + ), + "Vital Sign Plot" = list( + dataset = "vs", + vars = c( + analysis_param = "PARAM", + analysis_val = "AVAL", + analysis_date = "ADT", + analysis_indicator = "VISIT", + range_low_limit = NULL, + range_high_limit = NULL, + summary_stats = "AVAL_MEAN" + ), + tooltip = c( + "Vital sign Parameter: " = "PARAM", + "Vital sign Date: " = "ADT", + "Vital sign Visit: " = "AVISIT", + "
Vital sign Value: " = "AVAL", + "Vital sign mean value by visits: " = "AVAL_MEAN" + ) + ) + ) + ) + ) + ) + + dv.manager::run_app( + data = dataset_list, + module_list = module_list, + filter_data = "adsl" + ) +} diff --git a/R/mod_API.R b/R/mod_API.R new file mode 100644 index 0000000..dca406c --- /dev/null +++ b/R/mod_API.R @@ -0,0 +1,116 @@ +# Patient profile module interface description ---- +mod_patient_profile_API_docs <- list( + "PAtient PrOfile", + module_id = "", + subject_level_dataset_name = "", + subjid_var = "", + sender_ids = "Identifiers of modules allowed to request the display of target patient IDs", + summary = list( + "Subject-level summary section", + vars = "Values to display in the summary section", + column_count = "Column count for the summary section" + ), + listings = list( + "Listings section", + dataset = "", + default_vars = "Default columns to display. If not specified, the first six columns are selected by default" + ), + plots = list( + "Plot section", + timeline_info = list( + "Start and end study dates", + icf_date = "Informed Consent Form signing Date", + trt_start_date = "Treatment Start Date, used also as Day 1 Reference Date", + trt_end_date = "Treatment End Date", + part_end_date = "Participation End Date" + ), + range_plots = list( + "Plots for range-like events (adverse events, concomitant medications, ...)", + dataset = "", + vars = list( + "Variables of interest for the event", + start_date = "Start date", + end_date = "End date", + decode = "Descriptive event label", + grading = "Degree of the event, used for color-coding the plot", + serious_ae = "Marker of event seriousness, usually reserved for adverse event datasets" + ), + tooltip = "Block of text to display as hover information over the left edge of each range. The names of this list are included as literal text and honor three basic HTML formatting elements: ``, ``, `
`). The columns the values refer to are populated with the value on the dataset relevant to any given row" + ), + value_plots = list( + "Plots for value-like (lab measurements, vital signs, ...) traces", + dataset = "", + vars = list( + "Variables of interest for the trace", + analysis_param = "Parameter", + analysis_val = "Value", + analysis_date = "Date", + analysis_indicator = "Analysis reference range indicator", + range_low_limit = "Lower limit of the reference range", + range_high_limit = "Upper limit of the reference range", + summary_stats = "Additional value column for summary statistics" + ), + tooltip = "Block of text to display as hover information over each point of the trace. The names of this list are included as literal text and honor three basic HTML formatting elements: ``, ``, `
`). The columns the values refer to are populated with the value on the dataset relevant to any given row" + ), + vline_vars = "Place vertical dashed lines on days indicated by this dataset columns", + vline_day_numbers = "Place vertical dashed lines on days indicated by this parameter", + palette = "If a name on this list matches the text on a plot element, the associated color will be applied to that element. This mapping takes precedence over the built-in palette" + ) +) + +mod_patient_profile_API <- T_group( + module_id = T_mod_ID(), + subject_level_dataset_name = T_dataset_name() |> T_flag("subject_level_dataset_name"), + subjid_var = T_col("subject_level_dataset_name", T_or(T_factor(), T_character())) |> T_flag("subjid_var"), + sender_ids = T_character() |> T_flag("zero_or_more", "optional", "ignore"), + summary = T_group( + vars = T_col("subject_level_dataset_name") |> T_flag("zero_or_more", "as_array"), + column_count = T_integer(min = 1, max = 12) + ) |> T_flag("optional"), + listings = T_group( + dataset = T_dataset_name(), + default_vars = T_col("dataset") |> T_flag("optional", "zero_or_more", "as_array") + ) |> T_flag("optional", "zero_or_more", "named"), + plots = T_group( + timeline_info = T_group( + icf_date = T_col("subject_level_dataset_name", T_or(T_date(), T_datetime())) |> T_flag("optional"), + trt_start_date = T_col("subject_level_dataset_name", T_or(T_date(), T_datetime())), + trt_end_date = T_col("subject_level_dataset_name", T_or(T_date(), T_datetime())), + part_end_date = T_col("subject_level_dataset_name", T_or(T_date(), T_datetime())) |> T_flag("optional") + ) |> T_flag("as_array"), + range_plots = T_group( + dataset = T_dataset_name(), + vars = T_group( + start_date = T_col("dataset", T_or(T_date(), T_datetime())), + end_date = T_col("dataset", T_or(T_date(), T_datetime())), + decode = T_col("dataset", T_or(T_character(), T_factor())), + grading = T_col("dataset", T_or(T_character(), T_factor())) |> T_flag("optional"), + serious_ae = T_col("dataset", T_or(T_logical(), T_YN()) |> T_map_to(T_logical())) |> T_flag("optional") + ) |> T_flag("as_array"), + tooltip = T_col("dataset") |> T_flag("zero_or_more", "named", "as_array") + ) |> T_flag("zero_or_more", "named"), + value_plots = T_group( + dataset = T_dataset_name(), + vars = T_group( + analysis_param = T_col("dataset", T_or(T_character(), T_factor())), + analysis_val = T_col("dataset", T_numeric()), + analysis_date = T_col("dataset", T_or(T_date(), T_datetime())), + analysis_indicator = T_col("dataset", T_or(T_character(), T_factor())) |> T_flag("optional"), + range_low_limit = T_col("dataset", T_numeric()) |> T_flag("optional"), + range_high_limit = T_col("dataset", T_numeric()) |> T_flag("optional"), + summary_stats = T_col("dataset", T_numeric()) |> T_flag("optional") + ) |> T_flag("as_array"), + tooltip = T_col("dataset") |> T_flag("zero_or_more", "named", "as_array") + ) |> T_flag("zero_or_more", "named"), + vline_vars = T_col( + "subject_level_dataset_name", T_or(T_CDISC_study_day(), T_date(), T_datetime()) + ) |> T_flag("zero_or_more", "named", "as_array"), + vline_day_numbers = T_CDISC_study_day() |> T_flag("optional", "zero_or_more", "named", "as_array"), + palette = T_color() |> T_flag("optional", "zero_or_more", "named", "as_array") + ) |> T_flag("optional") +) |> T_attach_docs(mod_patient_profile_API_docs) + +# Available module specifications ---- +module_specifications <- list( + "dv.papo::mod_patient_profile" = mod_patient_profile_API # TODO: Add another module to demonstrate the generality of the approach +) diff --git a/R/mod_listing.R b/R/mod_listing.R new file mode 100644 index 0000000..376f472 --- /dev/null +++ b/R/mod_listing.R @@ -0,0 +1,222 @@ +#' Create user interface for patient listings shiny module of \pkg{dv.papo} +#' +#' @param id A unique ID string to create a namespace. Must match the ID of +#' \code{patient_plot_server()}. +#' +#' @keywords internal +#' +patient_listing_UI <- function(id) { # nolint + ns <- shiny::NS(id) + + shiny::uiOutput(ns("ui")) +} + +#' Create server for patient listings shiny module of \pkg{dv.papo} +#' +#' @param id A unique ID string to create a namespace. Must match the ID of +#' \code{patient_listing_UI()}. +#' @param data_list List of data frames containing data for each listing of selected patient. +#' @param key_value Character: Value of selected patient +#' @inheritParams mod_patient_profile +#' +#' @keywords internal +#' +patient_listing_server <- function(id, data_list, key_value, listings) { + shiny::moduleServer( + id, + function(input, output, session) { + ns <- session$ns + + testing <- isTRUE(getOption("shiny.testmode")) + if (testing) { + exported_test_data <- list() + shiny::exportTestValues(test_data = exported_test_data) + } + + shiny::setBookmarkExclude(c( + "table_cell_clicked", + "table_rows_current", + "table_rows_all", + "table_search", + "table_search_columns", + "table_rows_selected", + "table_cells_selected", + "table_columns_selected", + "table_state" + )) + + max_width <- 12 + + output[["ui"]] <- shiny::renderUI({ + shiny::req(length(listings) > 0) + ui <- list( + shiny::fluidRow( + shiny::column( + max_width, + shiny::h3("Data Listings"), + shiny::uiOutput(ns("data_selector_ui")) + ), + # column selector + shiny::uiOutput(ns("column_selector")), + shiny::column( + max_width, + # data listing + shiny::uiOutput(ns("listing_ui")) + ) + ), + shiny::br() + ) + return(ui) + }) + + output[["data_selector_ui"]] <- shiny::renderUI({ + shiny::req(data_list()) + choices <- c("N/A" = NA_character_) + if (length(listings) > 0) choices <- sapply(listings, function(listing) listing[["dataset"]]) + + shinyWidgets::radioGroupButtons( + inputId = ns("data_selector"), + label = "Select Domain:", + status = "primary", + selected = shiny::isolate(input[["data_selector"]]), + choices = choices + ) + }) + + column_selector_first_pass <- TRUE + + output[["column_selector"]] <- shiny::renderUI({ + shiny::req(data_list()) + + ui <- list() + + for (listing in listings) { + dataset_name <- listing[["dataset"]] + + dataset <- data_list()[[dataset_name]] + choices <- names(dataset) + labels <- sapply(choices, function(col) { + res <- attr(dataset[[col]], "label") + if (is.null(res)) res <- "" + return(res) + }) + + default_vars <- listing[["default_vars"]] + if (column_selector_first_pass) { + # if app creator specifies no columns, default selection is first six columns + if (length(default_vars) == 0) default_vars <- utils::head(choices, n = 6) + } + + sel_id <- paste0("column_selector_", dataset_name) + + selected <- default_vars + if (is.null(selected)) selected <- shiny::isolate(input[[sel_id]]) + + ui[[length(ui) + 1]] <- shiny::column( + max_width, + shiny::conditionalPanel( + paste0("input.data_selector == ", "'", dataset_name, "'"), + ns = ns, + shinyWidgets::pickerInput(ns(sel_id), + label = "Select Extra Columns", + choices = choices, + selected = selected, + choicesOpt = list(subtext = labels), + multiple = TRUE, + options = list("live-search" = TRUE, "actions-box" = TRUE) + ) + ) + ) + } + + if (column_selector_first_pass) { + # Consume defaults after first pass + for (i_listing in seq_along(listings)) { + listings[[i_listing]][["default_vars"]] <<- NULL + } + column_selector_first_pass <<- FALSE + } + + return(ui) + }) + + listing_contents <- shiny::reactive({ + dataset_name <- input[["data_selector"]] + shiny::req(dataset_name) + datasets <- data_list() + shiny::req(datasets) + data <- datasets[[dataset_name]] + shiny::req(data) + + columns <- input[[paste0("column_selector_", dataset_name)]] + + data <- data[columns] + + col_labels <- get_labels(data, columns) + + # replace NA labels with column Names + for (i in seq_along(col_labels)) { + if (is.na(col_labels[i])) col_labels[i] <- paste0(columns[i], " (No Label)") + } + + scroll_y <- if (nrow(data) > 10) "300" else FALSE + + if (testing) { + exported_test_data[["filtered_data"]] <<- data + } + + # turn character type into factor (to offer column filter options) + for (name in names(data)) { + if (is.character(data[[name]])) { + data[[name]] <- as.factor(data[[name]]) + } + } + + # styler: off + restore_original_order_js <- r"----( + function(e, dt, node, config) { + dt.iterator('table', function(s) { + s.aaSorting.length = 0; + s.aiDisplay.sort(function(a,b) { + return a-b; + }); + s.aiDisplayMaster.sort(function(a,b) { + return a-b; + }); + }).draw(); + } + )----" |> structure(class = c("character", "JS_EVAL")) + # styler: on + + res <- DT::datatable( + data = data, colnames = col_labels, + selection = "single", rownames = TRUE, + filter = "top", extensions = "Buttons", + options = list( + searching = TRUE, paging = FALSE, + scrollX = TRUE, scrollY = scroll_y, ordering = TRUE, + columnDefs = list(list(className = "dt-center", targets = "_all")), + dom = "Bfrtip", buttons = list(list( + extend = "collection", + text = "Reset Columns Order", + action = restore_original_order_js + )) + ) + ) + + return(res) + }) + + output[["listing_ui"]] <- shiny::renderUI({ + # DT::dataTableOutput can occupy a lot of space even if unpopulated, so we gate + # its inclusion by first checking if there is content to display in it + shiny::req(listing_contents()) + return(DT::dataTableOutput(ns("listing"))) + }) + + output[["listing"]] <- DT::renderDataTable({ + return(listing_contents()) + }) + } + ) +} diff --git a/R/mod_patient_info.R b/R/mod_patient_info.R new file mode 100644 index 0000000..d0e158d --- /dev/null +++ b/R/mod_patient_info.R @@ -0,0 +1,61 @@ +# NOTE(miguel): This shouldn't be a module. It has almost no functionality. It's only called once. + +#' Create user interface for the patient information shiny module of \pkg{dv.papo} +#' +#' @param id A unique ID string to create a namespace. Must match the ID of +#' \code{patient_info_server()}. +#' +#' @keywords internal +#' +#' @return A shiny \code{uiOutput} element. +patient_info_UI <- function(id) { # nolint + ns <- shiny::NS(id) + shiny::uiOutput(ns("ui_out")) +} + +#' Create server for the patient information shiny module of \pkg{dv.papo} +#' @param id A unique ID string to create a namespace. Must match the ID of +#' \code{patient_info_UI()}. +#' @param record row object of dataframe: row record for patient. +#' @param column_count A number indicating how many items should be in one row +#' +#' @keywords internal +#' +#' @inheritParams mod_patient_profile +patient_info_server <- function(id, record, subjid_var, column_count = 3) { + shiny::moduleServer( + id, + function(input, output, session) { + + # parts in ui_out + output$ui_out <- shiny::renderUI({ + shiny::req(nrow(record()) == 1 && ncol(record()) > 0) + + # content + digit_len <- 12 %/% column_count + pp_data <- record() + pp_cols <- names(pp_data) + pp_labels <- get_labels(pp_data) + + shiny::fluidRow( + shiny::column( + width = 12, + shiny::tagList( + shiny::h3("Patient Information"), + shiny::fluidRow( + lapply(seq_len(ncol(pp_data)), function(i) { + shiny::column( + digit_len, + shiny::tags$b(ifelse(is.na(pp_labels[i]), names(pp_data)[i], pp_labels[i])), + shiny::tags$b(": "), pp_data[[pp_cols[i]]] + ) + }) + ) + ), + shiny::br() + ) + ) + }) + } + ) +} diff --git a/R/mod_patient_profile.R b/R/mod_patient_profile.R new file mode 100644 index 0000000..da27b73 --- /dev/null +++ b/R/mod_patient_profile.R @@ -0,0 +1,384 @@ +#' Patient Profile Module UI +#' +#' (For use outside of the DaVinci framework)\cr +#' Places the Patient Profile module UI at the call site of this function. A matching call to [mod_patient_profile_server()] +#' is necessary.\cr +#' +#' @param id `[character]` Unique shiny ID. Must match the ID provided to [mod_patient_profile_server()]. +#' +#' @return Shiny UI. +#' +#' @seealso [mod_patient_profile()] and [mod_patient_profile_server()] +#' @export +mod_patient_profile_UI <- function(id) { # nolint + ns <- shiny::NS(id) + shiny::tagList( + shiny::uiOutput(ns("ui")), + patient_info_UI(ns("pp_ui_out")), + patient_listing_UI(ns("listings")), + patient_plot_UI(ns("plot_contents")) + ) +} + + +#' Patient Profile Module server +#' +#' (For use outside of the DaVinci framework)\cr +#' Runs the server that populates the UI returned by [mod_patient_profile_UI()].\cr +#' Requires a matching call to that function. +#' +#' @param id `[character]` Unique shiny ID. Must match the ID provided to [mod_patient_profile_UI()]. +#' @param subject_level_dataset `[reactive(data.frame)]` Visit-independent subject information. +#' @param extra_datasets `[reactive(data.frame(n))]` Visit-dependent subject datasets. +#' @inheritParams mod_patient_profile +#' @seealso [mod_patient_profile()] and [mod_patient_profile_UI()] +#' +#' @export +mod_patient_profile_server <- function(id, subject_level_dataset, extra_datasets, subjid_var, sender_ids, + summary, listings, plots) { + local({ + ac <- checkmate::makeAssertCollection() # nolint + checkmate::assert_class(subject_level_dataset, "reactive", add = ac) + checkmate::reportAssertions(ac) + }) + + timeline_info <- plots[["timeline_info"]] + range_plots <- plots[["range_plots"]] + value_plots <- plots[["value_plots"]] + vline_vars <- plots[["vline_vars"]] + vline_day_numbers <- plots[["vline_day_numbers"]] + palette <- plots[["palette"]] + + # NOTE: simplifies downstream code because list[[optional_missing_element]] returns NULL + for (i_plot in seq_along(range_plots)) { + if ("vars" %in% names(range_plots[[i_plot]])) { + range_plots[[i_plot]][["vars"]] <- as.list(range_plots[[i_plot]][["vars"]]) + } + } + for (i_plot in seq_along(value_plots)) { + if ("vars" %in% names(value_plots[[i_plot]])) { + value_plots[[i_plot]][["vars"]] <- as.list(value_plots[[i_plot]][["vars"]]) + } + } + + shiny::moduleServer( + id, + function(input, output, session) { + ns <- session[["ns"]] + + output[["ui"]] <- shiny::renderUI({ + res <- NULL + if (is.null(summary) && is.null(listings) && is.null(plots)) { + res <- list( + shiny::h2("Welcome to dv.papo"), + shiny::h3("Please provide at least one of these module parameters:"), + shiny::h4("\u2022 summary", style = "text-indent:2rem;"), + shiny::h4("\u2022 listings", style = "text-indent:2rem;"), + shiny::h4("\u2022 plots", style = "text-indent:2rem;"), + shiny::h3("They are all optional, but if none is provided there won't be much to look at.") + ) + } else { + res <- shiny::fluidRow( + shiny::column( + CONST$width_of_patient_selector_in_columns, + shiny::uiOutput(ns("selector")) + ) + ) + } + return(res) + }) + + output[["selector"]] <- shiny::renderUI({ + subject_level_dataset <- subject_level_dataset() + shiny::req(subject_level_dataset, cancelOutput = TRUE) + shiny::selectInput(ns("patient_selector"), + label = "Select Patient ID:", + selected = input[["patient_selector"]], + choices = unique(subject_level_dataset[[subjid_var]]) + ) + }) + + # change selected patient based on sender_ids + if (!is.null(sender_ids)) { + lapply(sender_ids, function(x) { + shiny::observeEvent(x()[["subj_id"]](), { + pid_passed <- x()[["subj_id"]]() + if (!identical(pid_passed, character(0))) { + shiny::updateSelectInput( + session = session, + inputId = "patient_selector", + selected = pid_passed + ) + } + }) + }) + } + + assert <- function(condition, message) shiny::validate(shiny::need(condition, message)) + + # patient info section + # reactive data for patient info + filtered_pt_info_data <- shiny::reactive({ + df <- subject_level_dataset() + excess_cols <- setdiff(summary$vars, names(df)) + assert( + length(excess_cols) == 0, + paste0( + "Error: `summary$vars` should be a subset of the columns available in ", + "the currently loaded subject-level dataframe (", + paste(names(df), collapse = ", "), ").\n", + "It contains the following unavailable columns: (", + paste(excess_cols, collapse = ", "), ")" + ) + ) + + pt_info_data_filter(df, subjid_var, summary$vars, input$patient_selector) + }) + + patient_info_server( + id = "pp_ui_out", + record = filtered_pt_info_data, + subjid_var = subjid_var, + column_count = summary$column_count + ) + + # reactive data for listings + filtered_listings_data <- shiny::reactive({ + shiny::req(input[["patient_selector"]]) + dataset_names <- sapply(listings, function(listing) listing[["dataset"]]) + out_list <- lapply(dataset_names, function(name) { + df <- extra_datasets()[[name]] + filter_with_mask(df, df[[subjid_var]] == input[["patient_selector"]]) + }) + names(out_list) <- dataset_names + return(out_list) + }) + + + # listings section + patient_listing_server( + id = "listings", + data_list = filtered_listings_data, + key_value = shiny::reactive(input$patient_selector), + listings = listings + ) + + # plots section + filtered_subject_level_dataset <- shiny::reactive({ + subject_id <- input[["patient_selector"]] + shiny::req(subject_id) + sl <- subject_level_dataset() + assert(subjid_var %in% names(sl), sprintf("Error: `subjid_var` variable %s not present in subject-level dataset", subjid_var)) + mask <- sl[[subjid_var]] == subject_id + assert(sum(mask) > 0, sprintf("Error: Selected patient returns no data")) + sl <- sl[sl[[subjid_var]] == subject_id, ] + return(sl) + }) + + filtered_extra_datasets <- shiny::reactive({ + subject_id <- input[["patient_selector"]] + shiny::req(subject_id) + + res <- list() + for (name in names(extra_datasets())) { + df <- extra_datasets()[[name]] + assert(subjid_var %in% names(df), sprintf("Error: `subjid_var` variable %s not present in dataset %s", subjid_var, name)) + res[[name]] <- df[df[[subjid_var]] == subject_id, ] + # rescue attributes dropped during subsetting + for (i in seq_along(res[[name]])) attributes(res[[name]][[i]]) <- attributes(df[[i]]) + } + return(res) + }) + + patient_plot_server( + id = "plot_contents", subjid_var, + subject_level_dataset = filtered_subject_level_dataset, + timeline_info, + extra_datasets = filtered_extra_datasets, + range_plots = range_plots, + value_plots = value_plots, + vline_vars = vline_vars, vline_day_numbers = vline_day_numbers, + palette = palette + ) + + return(NULL) + } + ) +} + +#' Patient Profile Module +#' +#' @description +#' +#' `mod_patient_profile` is a DaVinci Shiny module that displays patient information on a subject-level basis. It +#' consists of three sections: summary, listings and plots. +#' \itemize{ +#' \item The `summary` section shows visit-independent demographic information. +#' \item The `listings` section offers listings for visit-dependent information. +#' \item The `plots` section displays charts for events that happen over a span of time (adverse events, concomitant +#' medications, ...) or line plots of point-like events (laboratory values, vital sign measurements). +#' } +#' +#'
+#' Show/hide usage example +#'
+#'
+#' What follows is a sample call to the mod_patient_profile function. +#' See the main article of this package for a tutorial on how to parameterize it. +#' 
+#' dv.papo::mod_patient_profile(
+#'   module_id = "papo",
+#'   subject_level_dataset_name = "adsl",
+#'   subjid_var = "USUBJID",
+#'   summary = list(
+#'     vars = c("SUBJID", "SITEID", "ARM", "TRTSDT", "TRTEDT", "AGE", "RACE", "SEX", "BMIBL"),
+#'     column_count = 3L
+#'   ),
+#'   listings = list(
+#'     "Concomitant Medication" = list(
+#'       dataset = "cm"
+#'     ),
+#'     "Adverse Events" = list(
+#'       dataset = "adae",
+#'       default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV")
+#'     )
+#'   ),
+#'   plots = list(
+#'     timeline_info = c(trt_start_date = "TRTSDT", trt_end_date = "TRTEDT"),
+#'     range_plots = list(
+#'       "Concomitant Medication" = list(
+#'         dataset = "cm",
+#'         vars = c(
+#'           start_date = "CMSTDT", end_date = "CMENDT",
+#'           decode = "CMDECOD", grading = "CMDECOD"
+#'         ),
+#'         tooltip = c()
+#'       ),
+#'       "Adverse Events" = list(
+#'         dataset = "adae",
+#'         vars = c(
+#'           start_date = "ASTDT", end_date = "AENDT", decode = "AEDECOD",
+#'           grading = "AESEV", serious_ae = "AESER"
+#'         ),
+#'         tooltip = c("AE Start Day: " = "ASTDY", "AE End Day: " = "AENDY")
+#'       )
+#'     ),
+#'     value_plots = list(
+#'       "Lab Values" = list(
+#'         dataset = "lb",
+#'         vars = c(
+#'           analysis_param = "PARAM", analysis_val = "AVAL", analysis_date = "ADT",
+#'           analysis_indicator = "LBNRIND", range_low_limit = "A1LO", range_high_limit = "A1HI"
+#'         ),
+#'         tooltip = c()
+#'       )
+#'     ),
+#'     vline_vars = c(
+#'       "Informed Consent Date" = "RFICDT"
+#'     )
+#'   )
+#' )
+#'
+#'
+#'
+#'
+#' +#' +#' @inheritParams mod_patient_profile_params +#' +#' @return A list composed of the following elements: +#' \itemize{ +#' \item{`ui`}: Shiny UI function. +#' \item{`server`}: Shiny server function. +#' \item{`module_id`}: Shiny unique identifier. +#' } +#' +#' @seealso [mod_patient_profile_UI()], [mod_patient_profile_server()] +#' @export +mod_patient_profile <- function(module_id = "", + subject_level_dataset_name = NULL, + subjid_var = NULL, + sender_ids = NULL, + summary = NULL, + listings = NULL, + plots = NULL) { + args <- as.list(match.call()) # preserves `missing` behavior through reactives, saves us some typing + + # NOTE(miguel): These two lines allow the caller to provide lists whenever `mod_patient_profile_server` + # requires atomic arrays + args <- T_honor_as_array_flag(mod_patient_profile_API, args) + list2env(args[setdiff(seq_along(args), 1)], environment()) # overwrite current arguments with modified `args` + + mod <- list( + # UI function + ui = function(module_id) { + app_creator_feedback_ui(module_id) # NOTE: original UI gated by app_creator_feedback_server + }, + # Server function + server = function(afmm) { + fb <- shiny::reactive({ + # NOTE: We check the call here and not inside the module server function because: + # - app creators interact with the davinci module and not with the ui-server combo, so + # errors reported with respect to the module signature will make sense to them. + # The module server function might use a different function signature. + # - Here we also have access to the unfiltered dataset, which allows us to ensure call + # correctness independent of filter state or operation. + # Also, as long as the unfiltered dataset does not change (and to date no davinci app + # changes it dynamically) this check only runs once at the beginning of the application + # and has no further impact on performance. + # - "catch errors early" + + # Overwrite first "argument" (the function call, in fact) with the datasets provided to module manager + names(args)[[1]] <- "datasets" + args[[1]] <- afmm[["unfiltered_dataset"]]() + + do.call(check_papo_call, args) + }) + + fb_warn <- shiny::reactive(fb()[["warnings"]]) + fb_err <- shiny::reactive(fb()[["errors"]]) + + app_creator_feedback_server( + id = module_id, + warning_messages = fb_warn, + error_messages = fb_err, + ui = dv.papo::mod_patient_profile_UI(module_id) + ) + + filtered_mapped_datasets <- shiny::reactive( + T_honor_map_to_flag(afmm$filtered_dataset(), mod_patient_profile_API, args) + ) + + subject_level_dataset <- shiny::reactive({ + ds <- filtered_mapped_datasets()[[subject_level_dataset_name]] + shiny::validate( + shiny::need(!is.null(ds), paste("Could not find dataset", subject_level_dataset_name)) + ) + return(ds) + }) + + extra_datasets <- shiny::reactive({ + datasets <- filtered_mapped_datasets() + plot_dataset_names <- names(datasets) + return(datasets[plot_dataset_names]) + }) + + dv.papo::mod_patient_profile_server( + id = module_id, + subject_level_dataset = subject_level_dataset, + extra_datasets = extra_datasets, + subjid_var = subjid_var, + sender_ids = lapply(sender_ids, function(x) { + shiny::reactive(afmm[["module_output"]]()[[x]]) + }), + summary = summary, + listings = listings, + plots = plots + ) + }, + + # Module ID + module_id = module_id + ) + return(mod) +} diff --git a/R/mod_plots.R b/R/mod_plots.R new file mode 100644 index 0000000..9fee7b6 --- /dev/null +++ b/R/mod_plots.R @@ -0,0 +1,487 @@ +#' Create user interface for patient plot shiny module of \pkg{dv.papo} +#' +#' @param id A unique ID string to create a namespace. Must match the ID of +#' \code{patient_plot_server()}. +#' @param title character: Title of plot module +#' +#' @keywords internal +#' +patient_plot_UI <- function(id) { # nolint + ns <- shiny::NS(id) + + shiny::uiOutput(ns("ui")) +} + + +#' Create server for patient plot shiny module of \pkg{dv.papo} +#' +#' TODO: Document params (inherit them) +#' +#' @keywords internal +#' +#' +patient_plot_server <- function(id, subject_var, + subject_level_dataset, timeline_info, + extra_datasets, range_plots, value_plots, + vline_vars, vline_day_numbers, palette) { + shiny::moduleServer( + id, + function(input, output, session) { + ns <- session[["ns"]] + + # When testing reactivity, the usual way of looking at the state of a module is to isolate variables of interest + # into reactives of their own and then expose them through exportTestValues. This is a less invasive approach. + # We create a regular, non-reactive list and ... [continued in #ipahbo] + testing <- isTRUE(getOption("shiny.testmode")) + if (testing) { + exported_test_data <- list() + shiny::exportTestValues(test_plot_data = exported_test_data) + } + + palette <- unlist(utils::modifyList(as.list(CONST[["default_palette"]]), as.list(palette))) # user palette complements default + + v_extra_datasets <- shiny::reactive({ + extra_datasets <- extra_datasets() + for (df in extra_datasets) { + for (plot in c(range_plots, value_plots)) { + plot_cols <- append(plot$vars, subject_var) + ensure_columns_exist(extra_datasets[[plot$dataset]], unlist(plot_cols)) + + date_cols <- c(plot$vars$start_date, plot$vars$end_date, plot$vars$analysis_date) + ensure_columns_are_dates_or_datetimes(extra_datasets[[plot$dataset]], date_cols) + + numeric_cols <- c( + plot$vars$analysis_val, plot$vars$range_low_limit, + plot$vars$range_high_limit + ) + ensure_columns_are_numeric(extra_datasets[[plot$dataset]], numeric_cols) + } + } + return(extra_datasets) + }) + + sanitize_id <- function(id) gsub("[^a-zA-Z0-9_]", "", id) + + output[["ui"]] <- shiny::renderUI({ + shiny::req(!is.null(timeline_info)) + shiny::tagList( + shiny::h3("Graphical Display"), + shiny::fluidRow( + shiny::uiOutput(ns("selectors")) + ), + shiny::htmlOutput(ns("text")), + plotly::plotlyOutput(ns("plot")), + shiny::br() + ) + }) + + # Selectors for vs+lab plots. + output[["selectors"]] <- shiny::renderUI({ + extra_datasets <- v_extra_datasets() + selectors <- list() + + for (plot_name in names(value_plots)) { + plot <- value_plots[[plot_name]] + + dataset_name <- plot[["dataset"]] + param_col <- plot[["vars"]][["analysis_param"]] + choices <- sort(unique(extra_datasets[[dataset_name]][[param_col]])) # TODO: Enforce factor and use levels in the original order + + selector_id <- sanitize_id(plot_name) + selectors[[length(selectors) + 1]] <- shiny::column( + 3, + shinyWidgets::pickerInput( + inputId = ns(selector_id), + label = paste0("Please Select Parameter for ", plot_name, ":"), + choices = choices, + selected = shiny::isolate(input[[selector_id]]), + multiple = TRUE, + options = list("live-search" = TRUE, "actions-box" = TRUE) + ) + ) + } + + return(selectors) + }) + + compute_plots_and_messages <- function(subject_level_dataset, extra_datasets, vs_lb_selected) { + # TODO: Remove the messages already guarded against by check_papo_call + messages <- character(0) + plots <- list() + + # Process subject_level_dataset ---- + err <- ensure_columns_exist(subject_level_dataset, timeline_info, + flag_column_function = flag_columns_capture_error + ) + if (!is.null(err)) { + return(list(plots = list(), messages = err)) + } # fatal error + + timeline_info_names <- names(timeline_info) + date_cols <- timeline_info[endsWith(timeline_info_names, "date")] + err <- ensure_columns_are_dates_or_datetimes(subject_level_dataset, date_cols, + flag_column_function = flag_columns_capture_error + ) + if (!is.null(err)) { + return(list(plots = list(), messages = err)) + } # fatal error + + sl_info <- local({ + # map date-times to dates and warn about loss of precision + res <- subject_level_dataset + for (col in date_cols) { + if (inherits(res[[col]], "POSIXt")) { + date <- as.Date(res[[col]]) + if (as.POSIXct(date) != res[[col]]) { + # just a warning + messages[[length(messages) + 1]] <<- paste0("* Date-time column `", col, "` rounded to nearest date.") + } + res[[col]] <- date + } + } + + # use internal names for timeline columns (copied and not renamed to cope with repeat elements) + for (i_col in seq_along(timeline_info)) { + dest <- names(timeline_info)[[i_col]] + orig <- timeline_info[[i_col]] + res[[dest]] <- res[[orig]] + } + + return(res) + }) + + # Compute plots ---- + + timeline_limits <- local({ # start...end, but takes icf and part_end dates into account if available + min_total <- subject_level_dataset[[timeline_info[["trt_start_date"]]]] + if ("icf_date" %in% names(timeline_info)) { + icf_date <- subject_level_dataset[[timeline_info[["icf_date"]]]] + if (is.finite(icf_date)) min_total <- icf_date + } + + max_total <- as.Date(-Inf) + trt_end_date <- subject_level_dataset[[timeline_info[["trt_end_date"]]]] + if (is.finite(trt_end_date)) { + max_total <- trt_end_date + } + if ("part_end_date" %in% names(timeline_info)) { + part_end_date <- subject_level_dataset[[timeline_info[["part_end_date"]]]] + if (is.finite(part_end_date)) max_total <- part_end_date + } + if (!is.finite(max_total)) max_total <- Sys.Date() + + c(min_total, max_total) + }) + + x_limits <- local({ # we need to compute combined limits first because ggplot+plotly need them before layout calculation + # the +/-1 avoids clipping the left and right arrows on the plot + diff <- timeline_limits[[2]] - timeline_limits[[1]] + offset_left <- min(-1L, round(-diff / 10)) + offset_right <- max(1L, round(diff / 10)) + c(timeline_limits[[1]] + offset_left, timeline_limits[[2]] + offset_right) + }) + + plot_list <- local({ + res <- list() + + build_tooltip <- function(tooltip_spec, df) { + # TODO: color = .data[[plots[[set]]$vars$grading]] ?? + + res <- list() + for (i_row in seq_len(nrow(df))) { + res_elem <- "" + for (i_line in seq_along(tooltip_spec)) { + prefix <- names(tooltip_spec)[[i_line]] # NOTE: App creators can specify breaking lines through '
' + col <- tooltip_spec[[i_line]] + res_elem <- paste0(res_elem, prefix, df[[col]][[i_row]], "
") + } + res[[i_row]] <- res_elem + } + + return(res) + } + + # AE, CM + for (plot_name in names(range_plots)) { + plot_params <- range_plots[[plot_name]] + df <- extra_datasets[[plot_params$dataset]] + + if (nrow(df) == 0) { + messages[[length(messages) + 1]] <<- paste0("* No Data for ", plot_name, ".") + next + } + + # Column aliases (copied and not renamed to cope with repeat elements) + vars <- plot_params[["vars"]] + df[["start_date"]] <- as.Date(df[[vars[["start_date"]]]]) + df[["end_date"]] <- as.Date(df[[vars[["end_date"]]]]) + df[["decode"]] <- df[[vars[["decode"]]]] + if ("grading" %in% names(vars)) df[["grading"]] <- df[[vars[["grading"]]]] + if ("serious_ae" %in% names(vars)) df[["serious_ae"]] <- df[[vars[["serious_ae"]]]] + + # wrap decode column + df[["decode"]] <- strwrap(df[["decode"]], + width = CONST$decode_max_width_before_wrap_in_characters, + simplify = FALSE + ) |> sapply(function(x) paste(x, collapse = "\n")) + + df <- df[intersect(names(df), c("start_date", "end_date", "decode", "grading", "serious_ae"))] + + # Add `arrow_left` and `arrow_right` columns to range_plots + unknown_start_date <- is.na(df[["start_date"]]) + predate_study_start_date <- df[["start_date"]] < timeline_limits[[1]] + + df[["arrow_left"]] <- as.Date(NA) # no arrow + df[unknown_start_date | predate_study_start_date, "arrow_left"] <- timeline_limits[[1]] + df[unknown_start_date | predate_study_start_date, "start_date"] <- timeline_limits[[1]] + + unknown_end_date <- is.na(df[["end_date"]]) + outlast_study_end_date <- timeline_limits[[2]] < df[["end_date"]] + + df[["arrow_right"]] <- as.Date(NA) # no arrow + df[unknown_end_date | outlast_study_end_date, "arrow_right"] <- timeline_limits[[2]] + df[unknown_end_date | outlast_study_end_date, "end_date"] <- timeline_limits[[2]] + + y_count <- length(unique(df[["decode"]])) + height <- max(y_count + 2, 5) + + ggplot <- create_ae_cm_plot( + data = df, x_limits = x_limits, palette = palette, + sl_info, vline_vars = vline_vars, vline_day_numbers = vline_day_numbers, + ref_date = sl_info[["trt_start_date"]] + ) + + tooltip_text <- build_tooltip( + tooltip_spec = plot_params$tooltip, + df = extra_datasets[[plot_params$dataset]] + ) + + ggplot <- ggplot + ggplot2::aes(text = tooltip_text) + + plot <- plotly::ggplotly( + ggplot, + height = height * 32, tooltip = c("text") + ) + plot <- plotly::add_annotations( + plot, + text = plot_name, + x = 0, + y = 1, + yref = "paper", + xref = "paper", + xanchor = "left", + yanchor = "top", + xshift = 0, + yshift = 22, + showarrow = FALSE, + font = list(size = 15) + ) + + # ... [continued from #ipahbo] we just dump stuff into it from inside reactives wherever the + # variable of interest becomes available. Then ... [continued on tests/testthat/test-all.R:#umeega] + if (testing) { + exported_test_data[[paste0("tooltips/", plot_name)]] <<- tooltip_text + exported_test_data[[paste0("plot_first_line_color/", plot_name)]] <<- + plot[["x"]][["data"]][[1]][["line"]][["color"]] + exported_test_data[[paste0("arrow_right/", plot_name)]] <<- df[["arrow_right"]] + } + + # tweak legend manually - adapted from dv.papo 1; maybe there's a documented way of achieving the same? + extract_first <- function(s) sub("\\(([^,]*).*\\)", "\\1", s) + + for (i in seq_along(plot$x$data)) { + s <- plot$x$data[[i]]$name + if (!is.null(s)) plot$x$data[[i]]$name <- extract_first(s) + } + res[[length(res) + 1]] <- plot + } + + # VS, LAB + for (plot_name in names(value_plots)) { + plot_info <- value_plots[[plot_name]] + params <- vs_lb_selected[[sanitize_id(plot_name)]] + + if (length(params) == 0) { + messages[[length(messages) + 1]] <<- paste("* No Parameter for", plot_name, "selected.") + next + } + + for (i_param in seq_along(params)) { + local_palette <- palette + + param <- params[[i_param]] + df <- extra_datasets[[plot_info$dataset]] + + analysis_indicator_col <- plot_info[["vars"]][["analysis_indicator"]] + if (!is.null(analysis_indicator_col)) { + values <- df[[analysis_indicator_col]] + if (is.character(values)) { + values <- as.factor(values) + sprintf( + paste( + "* Analysis indicator column `%s` on dataset `%s` promoted to factor automatically.", + "Make it a factor beforehand to avoid this message." + ), + analysis_indicator_col, plot_info$dataset + ) |> warning() + } + + df[["analysis_indicator"]] <- values + + analysis_indicator_levels <- levels(values) + if ("" %in% trimws(analysis_indicator_levels)) { + sprintf( + "* Analysis indicator column `%s` on dataset `%s` Contains empty levels.", + analysis_indicator_col, plot_info$dataset + ) |> warning() + } + + levels_wo_palette_colors <- setdiff(levels(values), names(local_palette)) + if (length(levels_wo_palette_colors)) { + auto_color <- CONST$color_for_missing_analysis_indicator_levels + sprintf( + paste0( + "* Missing palette colors for analysis indicator column levels: ", + paste(levels_wo_palette_colors, collapse = ", "), ". Will paint them as %s." + ), auto_color + ) |> warning() + local_palette[levels_wo_palette_colors] <- auto_color + } + } + + param_mask <- df[[plot_info[["vars"]][["analysis_param"]]]] %in% param + df <- df[param_mask, ] + + ggplot <- create_lb_vs_plot( + data = df, + date = plot_info$vars[["analysis_date"]], + val = plot_info$vars[["analysis_val"]], + low_limit = plot_info$vars[["range_low_limit"]], + high_limit = plot_info$vars[["range_high_limit"]], + param = plot_info$vars[["analysis_param"]], + summary_stats = plot_info$vars[["summary_stats"]], + x_limits = x_limits, + palette = local_palette, + sl_info, vline_vars, + vline_day_numbers = vline_day_numbers, + ref_date = sl_info[["trt_start_date"]] + ) + + tooltip_text <- local({ + mask <- df[[plot_info$vars[["analysis_param"]]]] == param # TODO: this could precede the create_lb_vs_plot call #peizai + build_tooltip(tooltip_spec = plot_info$tooltip, df = df[mask, ]) + }) + + ggplot <- ggplot + ggplot2::aes(text = tooltip_text) + + plot <- plotly::ggplotly(ggplot, height = 160, tooltip = c("text")) + + plot <- plotly::add_annotations( + plot, + text = ifelse(i_param == 1, plot_name, ""), + x = 0, + y = 1, + yref = "paper", + xref = "paper", + xanchor = "left", + yanchor = "top", + xshift = 0, + yshift = 22, + showarrow = FALSE, + font = list(size = 15) + ) + + res[[length(res) + 1]] <- plot + } + } + + return(res) + }) + + if (length(plot_list)) { + # stack plots + heights <- sapply(plot_list, function(x) x[["height"]], simplify = "array") + heights <- heights + 80 / length(heights) # (HACK to cope with plotly) Divide space dedicated to footer equally among all plots + plots <- plotly::subplot(plot_list, + shareX = TRUE, titleX = TRUE, nrows = length(plot_list), margin = 0, + heights = heights / sum(heights) + ) + + x_limits_z <- x_limits - sl_info[["trt_start_date"]] + plots <- silence_warning( + plotly::layout(plots, height = sum(heights), xaxis = list(range = x_limits_z)), + "Specifying width/height in layout() is now deprecated.\nPlease specify in ggplotly() or plot_ly()" + # Bypass deprecation warning, because the alternative is using the size of one of the subplots to dictate the size + # of the stacked plot. This issue predates the covid pandemic and remains unresolved: + # https://github.com/plotly/plotly.R/issues/1613 + ) + + # strip unwanted portions of text (e.g. "(SCREENING 1,1)" -> "SCREENING 1") # TODO: where do these come from? + plots <- local({ + first_elem_before_comma_in_parens_re <- "\\(([^,]*),.*\\)" + for (i in seq_along(plots$x$data)) { + plots$x$data[[i]]$name <- sub(first_elem_before_comma_in_parens_re, "\\1", plots$x$data[[i]]$name) + } + plots + }) + + # remove legend duplicates # TODO: avoid including them in the first place? + plots <- local({ + names_seen <- character(0) + for (i in seq_along(plots$x$data)) { + name <- plots$x$data[[i]][["name"]] + if (name %in% names_seen) { + plots$x$data[[i]]$showlegend <- FALSE + } else { + names_seen <- c(names_seen, name) + } + } + plots + }) + + # title also gets duplicated when subplot joins legends # TODO: Avoid it to begin with + plots[["x"]][["layout"]][["legend"]][["title"]][["text"]] <- " Legend " + } + + return(list(plots = plots, messages = messages)) + } + + plots_and_messages <- shiny::reactive({ + if (length(range_plots) > 0 || length(value_plots) > 0) { + subject_level_dataset <- subject_level_dataset() + extra_datasets <- v_extra_datasets() + vs_lb_selected <- local({ + ids <- sanitize_id(names(value_plots)) + res <- Map(function(id) input[[id]], ids) + can_proceed <- setequal(intersect(ids, shiny::isolate(names(input))), ids) + shiny::req(isTRUE(can_proceed)) + return(res) + }) + + res <- shiny::maskReactiveContext( + compute_plots_and_messages(subject_level_dataset, extra_datasets, vs_lb_selected) + ) + } else { + res <- list(messages = "* No range or value plots configured") + } + + if (testing) { + exported_test_data[["plot_messages"]] <<- res[["messages"]] + } + + return(res) + }) + + output[["plot"]] <- plotly::renderPlotly({ + plots <- plots_and_messages()[["plots"]] + shiny::req(length(plots) > 0) + return(plots) + }) + + output[["text"]] <- shiny::renderUI({ + messages <- plots_and_messages()[["messages"]] + shiny::HTML(paste(messages, collapse = "
")) + }) + } + ) +} diff --git a/R/mod_signature.R b/R/mod_signature.R new file mode 100644 index 0000000..962ab2f --- /dev/null +++ b/R/mod_signature.R @@ -0,0 +1,171 @@ +#' Dummy function to extract parameter documentation from mod_patient_profile_API +#' +#' Generated by `write_mod_param_help.R`. +#' +#' @keywords internal +#' +#' @param module_id +#' `[character]` +#' Unique Shiny module identifier. +#' @param subject_level_dataset_name +#' `[character]` +#' Subject-level dataset name. +#' @param subjid_var +#' `[character]` +#' Unique subject identifier column. +#' @param sender_ids +#' `[character(n)]` (optional) +#' Identifiers of modules allowed to request the display of target patient IDs. +#' @param summary +#' `[list]` (optional) +#' Subject-level summary section. +#' Composed of: +#' * vars +#' `[character(n)]` +#' Values to display in the summary section. +#' Indexes into dataset `subject_level_dataset_name`. +#' * column_count +#' `[integer]` +#' Column count for the summary section. +#' @param listings +#' `[list(n)]` (optional) +#' Listings section. +#' Composed of: +#' * dataset +#' `[character]` +#' Dataset name. +#' * default_vars +#' `[character(n)]` (optional) +#' Default columns to display. If not specified, the first six columns are +#' selected by default. +#' Indexes into dataset `dataset`. +#' @param plots +#' `[list]` (optional) +#' Plot section. +#' Composed of: +#' * timeline_info +#' `[list]` +#' Start and end study dates. +#' Composed of: +#' * icf_date +#' `[character]` (optional) +#' Informed Consent Form signing Date. +#' Indexes into dataset `subject_level_dataset_name`. Expects `[Date|POSIXt]` +#' values. +#' * trt_start_date +#' `[character]` +#' Treatment Start Date, used also as Day 1 Reference Date. +#' Indexes into dataset `subject_level_dataset_name`. Expects `[Date|POSIXt]` +#' values. +#' * trt_end_date +#' `[character]` +#' Treatment End Date. +#' Indexes into dataset `subject_level_dataset_name`. Expects `[Date|POSIXt]` +#' values. +#' * part_end_date +#' `[character]` (optional) +#' Participation End Date. +#' Indexes into dataset `subject_level_dataset_name`. Expects `[Date|POSIXt]` +#' values. +#' * range_plots +#' `[list(n)]` +#' Plots for range-like events (adverse events, concomitant medications, ...). +#' Composed of: +#' * dataset +#' `[character]` +#' Dataset name. +#' * vars +#' `[list]` +#' Variables of interest for the event. +#' Composed of: +#' * start_date +#' `[character]` +#' Start date. +#' Indexes into dataset `dataset`. Expects `[Date|POSIXt]` values. +#' * end_date +#' `[character]` +#' End date. +#' Indexes into dataset `dataset`. Expects `[Date|POSIXt]` values. +#' * decode +#' `[character]` +#' Descriptive event label. +#' Indexes into dataset `dataset`. Expects `[character|factor]` values. +#' * grading +#' `[character]` (optional) +#' Degree of the event, used for color-coding the plot. +#' Indexes into dataset `dataset`. Expects `[character|factor]` values. +#' * serious_ae +#' `[character]` (optional) +#' Marker of event seriousness, usually reserved for adverse event datasets. +#' Indexes into dataset `dataset`. Expects `[logical|"Y"/"N"]` values. +#' * tooltip +#' `[character(n)]` +#' Block of text to display as hover information over the left edge of each range. +#' The names of this list are included as literal text and honor three basic HTML +#' formatting elements: ``, ``, `
`). The columns the values refer to are +#' populated with the value on the dataset relevant to any given row. +#' Indexes into dataset `dataset`. +#' * value_plots +#' `[list(n)]` +#' Plots for value-like (lab measurements, vital signs, ...) traces. +#' Composed of: +#' * dataset +#' `[character]` +#' Dataset name. +#' * vars +#' `[list]` +#' Variables of interest for the trace. +#' Composed of: +#' * analysis_param +#' `[character]` +#' Parameter. +#' Indexes into dataset `dataset`. Expects `[character|factor]` values. +#' * analysis_val +#' `[character]` +#' Value. +#' Indexes into dataset `dataset`. Expects `[numeric]` values. +#' * analysis_date +#' `[character]` +#' Date. +#' Indexes into dataset `dataset`. Expects `[Date|POSIXt]` values. +#' * analysis_indicator +#' `[character]` (optional) +#' Analysis reference range indicator. +#' Indexes into dataset `dataset`. Expects `[character|factor]` values. +#' * range_low_limit +#' `[character]` (optional) +#' Lower limit of the reference range. +#' Indexes into dataset `dataset`. Expects `[numeric]` values. +#' * range_high_limit +#' `[character]` (optional) +#' Upper limit of the reference range. +#' Indexes into dataset `dataset`. Expects `[numeric]` values. +#' * summary_stats +#' `[character]` (optional) +#' Additional value column for summary statistics. +#' Indexes into dataset `dataset`. Expects `[numeric]` values. +#' * tooltip +#' `[character(n)]` +#' Block of text to display as hover information over each point of the trace. The +#' names of this list are included as literal text and honor three basic HTML +#' formatting elements: ``, ``, `
`). The columns the values refer to are +#' populated with the value on the dataset relevant to any given row. +#' Indexes into dataset `dataset`. +#' * vline_vars +#' `[character(n)]` +#' Place vertical dashed lines on days indicated by this dataset columns. +#' Indexes into dataset `subject_level_dataset_name`. Expects +#' `[integer|Date|POSIXt]` values. +#' * vline_day_numbers +#' `[integer(n)]` (optional) +#' Place vertical dashed lines on days indicated by this parameter. +#' Represents a CDISC (non-zero) Study Day. +#' * palette +#' `[character(n)]` (optional) +#' If a name on this list matches the text on a plot element, the associated color +#' will be applied to that element. This mapping takes precedence over the +#' built-in palette. +#' Contains either an HTML (#xxxxxx) or an R color. +#' +#' @return No return value. +mod_patient_profile_params <- function(module_id, subject_level_dataset_name, subjid_var, sender_ids, summary, listings, plots) NULL diff --git a/R/prep_safety_data.R b/R/prep_safety_data.R new file mode 100644 index 0000000..f19f92a --- /dev/null +++ b/R/prep_safety_data.R @@ -0,0 +1,66 @@ +#' Prepare safety data +#' +#' Modifiy safetyData's adsl, adae, and adcm dummy data for easy use within +#' \pkg{dv.clinlines}. +#' +#' @param n Number of rows to select from the adsl dataset. The first n rows will be +#' taken. Used to reduce runtime during development. +#' +#' @return A list of three data frames. +#' +#' @keywords internal +#' +#' @importFrom rlang .data + +prep_safety_data <- function(n = 200) { + if (!requireNamespace("dplyr")) { + stop("This function requires `dplyr`") + } + + adsl_info <- safetyData::adam_adsl[1:n, ] + adsl_info[["TRTSDT"]] <- robust_ymd(adsl_info[["TRTSDT"]]) |> structure(label = "Treatment Start Date") + adsl_info[["TRTEDT"]] <- robust_ymd(adsl_info[["TRTEDT"]], round_up = TRUE) |> structure(label = "Treatment End Date") + adsl_info[["RFICDT"]] <- robust_ymd(adsl_info[["RFSTDTC"]]) |> structure(label = "Informed Consent Date") + adsl_info[["TRTDUR"]] <- as.numeric(adsl_info[["TRTDUR"]]) |> structure(label = "Treatment duration (days)") + + subjects <- unique(adsl_info[["USUBJID"]]) + + # adae + known_adverse_event_start_date_mask <- !is.na(safetyData::adam_adae[["ASTDT"]]) + selected_subject_mask <- safetyData::adam_adae[["USUBJID"]] %in% subjects + adae_info <- safetyData::adam_adae[known_adverse_event_start_date_mask & selected_subject_mask, ] + aeser_attributes <- attributes(adae_info[["AESER"]]) + adae_info[["AESER"]] <- c("Y" = TRUE, "N" = FALSE)[adae_info[["AESER"]]] + attributes(adae_info[["AESER"]]) <- aeser_attributes + + # cm + known_cm_event_start_date_mask <- !is.na(safetyData::sdtm_cm[["CMSTDTC"]]) + selected_subject_mask <- safetyData::sdtm_cm[["USUBJID"]] %in% subjects + cm_info <- safetyData::sdtm_cm[known_cm_event_start_date_mask & selected_subject_mask, ] + + cm_info[["CMSTDT"]] <- robust_ymd(cm_info[["CMSTDTC"]]) + cm_info[["CMENDT"]] <- robust_ymd(cm_info[["CMENDTC"]], round_up = TRUE) + + # vs + vs_info <- safetyData::adam_advs |> + dplyr::left_join(safetyData::adam_advs |> + dplyr::group_by(.data[["USUBJID"]], .data[["PARAM"]], .data[["VISIT"]]) |> + dplyr::summarise(AVAL_MEAN = mean(as.numeric(.data$AVAL)), .groups = "drop") |> + dplyr::ungroup(), by = c("USUBJID", "PARAM", "VISIT")) + attr(vs_info[["AVAL_MEAN"]], "label") <- "Mean Value" + + + # lb + lb_info <- safetyData::adam_adlbc |> + dplyr::left_join(safetyData::adam_adlbc |> + dplyr::group_by(.data[["USUBJID"]], .data[["PARAM"]], .data[["VISIT"]]) |> + dplyr::summarise(AVAL_MEAN = mean(as.numeric(.data$AVAL)), .groups = "drop") |> + dplyr::ungroup(), by = c("USUBJID", "PARAM", "VISIT")) |> + dplyr::filter( + .data$USUBJID %in% adsl_info$USUBJID + ) + + attr(lb_info[["AVAL_MEAN"]], "label") <- "Mean Value" + + return(list(adsl = adsl_info, adae = adae_info, cm = cm_info, lb = lb_info, vs = vs_info)) +} diff --git a/R/utils-misc.R b/R/utils-misc.R new file mode 100644 index 0000000..4d46ba5 --- /dev/null +++ b/R/utils-misc.R @@ -0,0 +1,65 @@ +drop_columns_by_name <- function(df, col_names) { + df[col_names] <- list(NULL) + return(df) +} + +select_columns_by_name <- function(df, col_names) { + return(df[, col_names, drop = FALSE]) +} + +filter_with_mask <- function(df, mask) { + labels <- Map(function(col) attr(col, "label"), df) + res <- df[mask, ] + for (name in names(labels)) attr(res[[name]], "label") <- labels[[name]] + return(res) +} + +silence_warning <- function(expr, warning_message) { + withCallingHandlers( + expr, + warning = function(w) { + if (w$message != warning_message) { + NULL + } else { + invokeRestart("muffleWarning") + } + } + ) +} + +merge_with_no_duplicate_cols <- function(a, b, by) merge(a, b[c(by, setdiff(names(b), names(a)))], by) + +robust_min <- function(...) min(..., +Inf, na.rm = TRUE) # TODO: Remove if unused +robust_max <- function(...) max(..., -Inf, na.rm = TRUE) # TODO: Remove if unused + +robust_ymd <- function(data, round_up = FALSE) { + label <- attr(data, "label") + + data <- substr(data, 1, 10) + missing_day <- !is.na(data) & nchar(data) == 7 + missing_month_day <- !is.na(data) & nchar(data) == 4 + if (round_up) { # next month, next year + year <- as.integer(substr(data[missing_day], 1, 4)) + month <- as.integer(substr(data[missing_day], 6, 7)) + 1 + carry <- month == 13 + year[carry] <- year[carry] + 1 + month[carry] <- 1 + data[missing_day] <- sprintf("%04d-%02d", year, month) + + year <- as.integer(substr(data[missing_month_day], 1, 4)) + 1 + data[missing_month_day] <- sprintf("%04d", year) + } + + data[missing_month_day] <- paste0(data[missing_month_day], "-01-01") + data[missing_day] <- paste0(data[missing_day], "-01") + + data <- as.Date(data) + + if (round_up) { # one day before next month, before next year + data[missing_day | missing_month_day] <- data[missing_day | missing_month_day] - 1 + } + + attr(data, "label") <- label + + return(data) +} diff --git a/R/write_mod_signature.R b/R/write_mod_signature.R new file mode 100644 index 0000000..9c92048 --- /dev/null +++ b/R/write_mod_signature.R @@ -0,0 +1,79 @@ +write_mod_param_help_inner <- function(elem, depth = 1) { + docs <- attr(elem, "docs") + + indentation <- strrep(" ", times = depth) + + cardinality <- if (isTRUE(attr(elem, "zero_or_more"))) "(n)" else "" + + res <- sprintf("#' `[%s%s]`", docs[["type"]], cardinality) + + if (isTRUE(attr(elem, "optional"))) res <- paste(res, "(optional)") + + if (nchar(docs[["manual_desc"]]) > 0) { + manual_desc <- paste0(docs[["manual_desc"]], ".") + manual_desc <- paste("#' ", strwrap(manual_desc, width = 80)) + res <- c(res, manual_desc) + } + + if (length(docs[["auto_desc"]])) { + auto_desc <- paste0(docs[["auto_desc"]], ".") |> paste(collapse = " ") + auto_desc <- paste("#' ", strwrap(auto_desc, width = 80)) + res <- c(res, auto_desc) + } + + if (elem$kind == "group") { + res <- c(res, "#' Composed of:") + + subelem_names <- names(elem[["elements"]]) + for (i_elem in seq_along(elem[["elements"]])) { + subelem <- elem[["elements"]][[i_elem]] + res <- c( + res, + paste( + sprintf("#'%s*", indentation), + subelem_names[[i_elem]] + ), + write_mod_param_help_inner(subelem, depth + 1) + ) + } + } + + return(res) +} + +write_mod_param_help <- function() { + env <- new.env() + mod_API_path <- system.file("R/mod_API.R", package = "dv.papo", mustWork = TRUE) + source(mod_API_path, local = env) + api <- env[["mod_patient_profile_API"]][["elements"]] + + head <- c( + "#' Dummy function to extract parameter documentation from mod_patient_profile_API", + "#'", + "#' Generated by `write_mod_param_help.R`.", + "#'", + "#' @keywords internal", + "#'" + ) + + param_docs <- c() + + param_names <- names(api) + for (i_param in seq_along(api)) { + param_name <- param_names[[i_param]] + param <- api[[i_param]] + param_head <- paste("#' @param", param_name) + param_tail <- write_mod_param_help_inner(param) + param_docs <- c(param_docs, param_head, param_tail) + } + + tail <- c( + "#'", + "#' @return No return value.", + sprintf("mod_patient_profile_params <- function(%s) NULL", paste(names(api), collapse = ", ")) + ) + + mod_signature_path <- file.path(system.file("R", package = "dv.papo"), "mod_signature.R") + + writeLines(text = c(head, param_docs, tail), con = mod_signature_path) +} diff --git a/README.Rmd b/README.Rmd new file mode 100644 index 0000000..3cffa78 --- /dev/null +++ b/README.Rmd @@ -0,0 +1,91 @@ +--- +output: + md_document: + variant: markdown_github +--- + + + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>", + out.width = "100%", + tidy = "styler" +) +``` + +# dv.papo + + + + +DaVinci's `dv.papo` module shows patient information on a subject-level basis. + +It can produce listings as well as a variety of plots. Those include events over time (adverse events, concomitant medications, ...) or point-like events (lab values, vital sign measurements, ...). + +It is no limited to one data source, thus it can handle data from either ADAM, or SDTM. + +![](man/figures/patient_profile_app.png) + +Other DaVinci modules can direct `mod_patient_profile` to select and display information associated to any particular subject ID. When the Patient Profile is so instructed, it switches to the target subject ID and takes focus from the application, effectively *jumping* to a patient profile display as a result of a simple user interaction, such as a mouse click. + +## Installation + +``` r +if (!require("remotes")) install.packages("remotes") +remotes::install_github("Boehringer-Ingelheim/dv.papo") +``` + +## Example +To use `dv.papo` inside a DaVinci app, add the module to your module list. The code below shows an example definition of a one-item module list. The setup of the `plots` parameter produces a plot showing Adverse Events.
+See `vignette("a00-papo")` for further information on how to use `dv.papo` with `dv.manager`. + +```{r example, eval = FALSE} + dataset_list <- list( + "demo" = dv.papo:::prep_safety_data(5), + "demo2" = dv.papo:::prep_safety_data(10) + ) + + module_list <- list( + "Patient Profile" = dv.papo::mod_patient_profile( + module_id = "papo", + subject_level_dataset_name = "adsl", + subjid_var = "USUBJID", + summary = list( + vars = c("SUBJID", "SITEID", "ARM", "TRTSDT", "TRTEDT", "AGE", "RACE", "SEX", "BMIBL"), + column_count = 3L + ), + listings = list( + "Concomitant Medication" = list( + dataset = "cm" + ), + "Adverse Events" = list( + dataset = "adae", + default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV") + ) + ), + plots = list( + timeline_info = c(trt_start_date = "TRTSDT", trt_end_date = "TRTEDT"), + range_plots = list( + "Adverse Events" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", end_date = "AENDT", + decode = "AEDECOD", grading = "AESEV", serious_ae = "AESER" + ), + tooltip = c("AE Start Day: " = "ASTDY", "AE End Day: " = "AENDY") + ) + ), + value_plots = list(), + vline_vars = c("Informed Consent Date" = "RFICDT") + ) + ) + ) + + dv.manager::run_app( + data = dataset_list, + module_list = module_list, + filter_data = "adsl" + ) +``` diff --git a/README.md b/README.md index 4109864..23cb68c 100644 --- a/README.md +++ b/README.md @@ -1 +1,89 @@ + + # dv.papo + + + + +DaVinci’s `dv.papo` module shows patient information on a subject-level +basis. + +It can produce listings as well as a variety of plots. Those include +events over time (adverse events, concomitant medications, …) or +point-like events (lab values, vital sign measurements, …). + +It is no limited to one data source, thus it can handle data from either +ADAM, or SDTM. + +![](man/figures/patient_profile_app.png) + +Other DaVinci modules can direct `mod_patient_profile` to select and +display information associated to any particular subject ID. When the +Patient Profile is so instructed, it switches to the target subject ID +and takes focus from the application, effectively *jumping* to a patient +profile display as a result of a simple user interaction, such as a +mouse click. + +## Installation + +``` r +if (!require("remotes")) install.packages("remotes") +remotes::install_github("Boehringer-Ingelheim/dv.papo") +``` + +## Example + +To use `dv.papo` inside a DaVinci app, add the module to your module +list. The code below shows an example definition of a one-item module +list. The setup of the `plots` parameter produces a plot showing Adverse +Events.
See `vignette("a00-papo")` for further information on how +to use `dv.papo` with `dv.manager`. + +``` r +dataset_list <- list( + "demo" = dv.papo:::prep_safety_data(5), + "demo2" = dv.papo:::prep_safety_data(10) +) + +module_list <- list( + "Patient Profile" = dv.papo::mod_patient_profile( + module_id = "papo", + subject_level_dataset_name = "adsl", + subjid_var = "USUBJID", + summary = list( + vars = c("SUBJID", "SITEID", "ARM", "TRTSDT", "TRTEDT", "AGE", "RACE", "SEX", "BMIBL"), + column_count = 3L + ), + listings = list( + "Concomitant Medication" = list( + dataset = "cm" + ), + "Adverse Events" = list( + dataset = "adae", + default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV") + ) + ), + plots = list( + timeline_info = c(trt_start_date = "TRTSDT", trt_end_date = "TRTEDT"), + range_plots = list( + "Adverse Events" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", end_date = "AENDT", + decode = "AEDECOD", grading = "AESEV", serious_ae = "AESER" + ), + tooltip = c("AE Start Day: " = "ASTDY", "AE End Day: " = "AENDY") + ) + ), + value_plots = list(), + vline_vars = c("Informed Consent Date" = "RFICDT") + ) + ) +) + +dv.manager::run_app( + data = dataset_list, + module_list = module_list, + filter_data = "adsl" +) +``` diff --git a/_pkgdown.yml b/_pkgdown.yml new file mode 100644 index 0000000..068b1fd --- /dev/null +++ b/_pkgdown.yml @@ -0,0 +1,25 @@ +template: + bootstrap: 5 + +navbar: + type: inverse + structure: + left: [intro, reference, articles, tutorials, news, qc] + components: + qc: + text: Quality Control + href: articles/qc.html +home: + title: dv.papo + links: + +reference: +- title: Main module function +- contents: + - mod_patient_profile +- title: Functions for use outside of DaVinci +- contents: + - starts_with("mod_patient_profile_") +- title: Demo/configuration tool +- contents: + - explorer_app diff --git a/inst/validation/results/.gitempty b/inst/validation/results/.gitempty new file mode 100644 index 0000000..e69de29 diff --git a/inst/validation/run_validation.R b/inst/validation/run_validation.R new file mode 100644 index 0000000..465c65c --- /dev/null +++ b/inst/validation/run_validation.R @@ -0,0 +1,44 @@ +pkg_name <- read.dcf("DESCRIPTION")[, "Package"] +pkg_version <- read.dcf("DESCRIPTION")[, "Version"] +test_results <- tibble::as_tibble(devtools::test()) + +local({ + # This is evaluated inside a local because, otherwise, all the variables created in the chunks of the rendered + # document leak into the environment + + validation_root <- "./inst/validation" + validation_report_rmd <- file.path(validation_root, "val_report.Rmd") + validation_report_html <- "val_report.html" + validation_results <- file.path(validation_root, "results") + val_param_rds <- file.path(validation_results, "val_param.rds") + + stopifnot(dir.exists(validation_root)) + stopifnot(file.exists(validation_report_rmd)) + + stopifnot(dir.exists(validation_results)) + unlink(list.files(validation_results)) + + saveRDS( + list( + package = pkg_name, + tests = test_results, + version = pkg_version + ), + val_param_rds + ) + + rmarkdown::render( + input = validation_report_rmd, + params = list( + package = pkg_name, + tests = test_results, + version = pkg_version + ), + output_dir = validation_results, + output_file = validation_report_html + ) + + # We use one of the leaked variables, created inside the validation report to asses if the validation is + # succesful or not + VALIDATION_PASSED +}) diff --git a/inst/validation/specs.R b/inst/validation/specs.R new file mode 100644 index 0000000..1c4f26b --- /dev/null +++ b/inst/validation/specs.R @@ -0,0 +1,35 @@ +specs <- list( + common = list( + subject_selector = "The subject selector selects subjects", + bookmarking = "Bookmarks bookmark state", + jump_to_subject = "The jump-to-subject switches to subject when instructed", + misconfiguration_feedback = "The module shows informative messages when misconfigured", + dataset_change = "Patient selector updates after dataset change" + ), + summary = list( + columns = "Summary data presented in custom column count" + ), + listings = list( + column_labels = "Listings display column labels in headings if available", + switching = "Tab buttons allow listing switching", + filtering = "Listing content can be searched and filtered", + sorting = "Listing content can sorted and the order can be reset", + extra_column_selection = "User can modify columns included in listing", + extra_column_selection_labels = "Column selector shows dataset column labels", + no_data_message = "Listings explain there is no data when there is no data" + ), + plots = list( + common = list( + tooltips = "Hovering over salient plot elements provides extra information", + palettes = "Plots can be customized by assigning specific colors to elements denoted by text strings", + no_data_message = "Plots explain there is no data when there is no data" + ), + value = list( + parameter_selection = "User can select parameters for value plots" + ), + range = list( + arrows = "Arrows indicate events exceeding range limits", + grading = "Plots colored according to grading" + ) + ) +) diff --git a/inst/validation/utils-validation.R b/inst/validation/utils-validation.R new file mode 100644 index 0000000..06eeb3d --- /dev/null +++ b/inst/validation/utils-validation.R @@ -0,0 +1,155 @@ +#' Setting up the validation + +if (!exists("package_name")) stop("package name must be in the environment when this script is sourced") + +#' How to link tests and specs + +if (FALSE) { + test_that( + vdoc[["add_spec"]]("my test description", specs$a_spec), + { + expect_true(TRUE) + } + ) +} +#' The specs variable on the call references the one declared in specs.R + +#' 3. For those tests covering more than one spec. +#' NOTE: It must be c() and not list() +#' + +if (FALSE) { + test_that( + vdoc[["add_spec"]]("my test_description", c(specs$my$hier$spec, vdoc_specs$my$hier$other_spec)), + { + expect_true(TRUE) + } + ) +} + +#' Considerations: +#' - parse_spec uses deparse(substitute()). These spec_ids are later used to check if all requirements +#' are covered or not, therefore those calls cannot by substituted for: + +if (FALSE) { + my_spec <- specs$my$hier$spec + test_that(vdoc[["add_spec"]]("my test_description", my_spec), { + ... + }) + + test_that(vdoc[["add_spec"]]("my test_description", specs[["my"]][["hier"]][["spec"]]), { + ... + }) +} + +# In this case the substitute captures my_spec and cannot be used later. +# If you want to do this you must use the spec_id parameter where you pass a +# character vector with the ids. +# Notice that the ids in character form do no longer have the specs particle +# at the beginning, only the pathing of the spec is needed. + +if (FALSE) { + my_spec <- specs$my$hier$spec + test_that(vdoc$parse_spec(my_spec, "my test_description", spec_id = c("my$hier$spec")), { + ... + }) +} + +# Validation code +# nolint start cyclocomp_linter +local({ + specs <- source( + system.file("validation", "specs.R", package = package_name, mustWork = TRUE), + local = TRUE + )[["value"]] + recursive_ids <- function(x, parent = character(0)) { + if (!is.list(x)) { + return(parent) + } + unlist(mapply(recursive_ids, + x, + paste(parent, names(x), + sep = if (identical(parent, character(0))) "" else "$" + ), + SIMPLIFY = FALSE, USE.NAMES = FALSE + )) + } + + recursive_ids <- function(x, parent = character(0)) { + if (!is.list(x)) { + return(parent) + } + unlist(mapply(recursive_ids, x, + paste(parent, names(x), + sep = if (identical(parent, character(0))) "" else "$" + ), + SIMPLIFY = FALSE, USE.NAMES = FALSE + )) + } + + + spec_id_list <- recursive_ids(specs) + + list( + specs = specs, + spec_id_list = spec_id_list, + add_spec = function(desc, spec, spec_id) { + if (missing(spec_id)) { + if (!is.character(spec) || length(spec) == 0) stop("spec must be a non-empty character vector") + s_spec <- substitute(spec) + if (s_spec[[1]] == "c") { + spec_id <- sapply(s_spec[2:length(s_spec)], identity) + } else { + spec_id <- list(s_spec) # Otherwise the posterior vapply iterates over the expression + } + + spec_id_chr <- vapply(spec_id, function(x) { + sub("^[^$]*\\$", "", deparse(x)) + }, FUN.VALUE = character(1)) + + if (!all(spec_id_chr %in% spec_id_list)) { + stop("At least one spec is not declared in the spec list") + } # This should be covered by pack of constants but just in case + } else { + spec_id_chr <- spec_id + } + paste0(desc, "__spec_ids{", paste0(spec_id_chr, collapse = ";"), "}") + }, + get_spec = function(test, specs) { + spec_ids <- utils::strcapture( + pattern = "__spec_ids\\{(.*)\\}", + x = test, + proto = list(spec = character()) + )[["spec"]] + + spec_ids <- strsplit(spec_ids, split = ";") + + specs_and_id <- list() + + for (idx in seq_along(spec_ids)){ + ids <- spec_ids[[idx]] + if (all(!is.na(ids))) { + this_specs <- list() + for (sub_idx in seq_along(ids)) { + id <- ids[[sub_idx]] + this_specs[[sub_idx]] <- eval(str2expression(paste0("specs$", id))) + } + specs_and_id[[idx]] <- list( + spec_id = ids, + spec = this_specs + ) + } else { + specs_and_id[[idx]] <- list( + spec_id = NULL, + spec = NULL + ) + } + } + specs_and_id + } + + + ) +}) + +# nolint end cyclocomp_linter \ No newline at end of file diff --git a/inst/validation/val_report.Rmd b/inst/validation/val_report.Rmd new file mode 100644 index 0000000..26a97e9 --- /dev/null +++ b/inst/validation/val_report.Rmd @@ -0,0 +1,17 @@ +--- +title: "Quality Control" +output: + html_document: + toc: true + toc_depth: 2 + code_folding: hide +toc-title: "----\nIndex" + +params: + package: NULL + tests: NULL + version: NULL +--- + +```{r, child = "val_report_child.Rmd"} +``` diff --git a/inst/validation/val_report_child.Rmd b/inst/validation/val_report_child.Rmd new file mode 100644 index 0000000..bf7f1bc --- /dev/null +++ b/inst/validation/val_report_child.Rmd @@ -0,0 +1,209 @@ + + + +```{r setup, message = FALSE} +# Import vdoc functions ---- +vdoc <- local({ + # ########## + # package_name is used # INSIDE # the sourced file below + # ########## + package_name <- params[["package"]] + utils_file_path <- system.file("validation", "utils-validation.R", package = package_name, mustWork = TRUE) + source(utils_file_path, local = TRUE)[["value"]] +}) + +# Set required packages ---- +suppressPackageStartupMessages(stopifnot(requireNamespace("DT"))) +suppressPackageStartupMessages(stopifnot(requireNamespace("devtools"))) + +# Parse tests ---- + +tests <- as.data.frame(params[["tests"]]) +tests[["validation_data"]] <- vdoc[["get_spec"]](tests[["test"]], vdoc[["specs"]]) +tests[["spec_id"]] <- sapply(tests[["validation_data"]], function(x) x[["spec_id"]]) +tests[["spec"]] <- sapply(tests[["validation_data"]], function(x) x[["spec"]]) +tests[["spec_id_paste"]] <- vapply(tests[["spec_id"]], function(x) paste(x, collapse = "\n"), FUN.VALUE = character(1)) +tests[["spec_paste"]] <- vapply(tests[["spec"]], function(x) paste(x, collapse = "\n"), FUN.VALUE = character(1)) +tests[["desc"]] <- paste0("(#", seq_len(nrow(tests)), "): ", tests[["test"]]) +tests[["with_spec"]] <- vapply(tests[["spec_id"]], Negate(is.null), FUN.VALUE = logical(1)) + +spec_tests <- tests[tests[["with_spec"]], ] +no_spec_tests <- tests[!tests[["with_spec"]], ] + +declared_spec <- vdoc[["spec_id_list"]] +tested_spec <- unique(unlist(tests[["spec_id"]])) +uncovered_spec <- declared_spec[!declared_spec %in% tested_spec] +undeclared_spec <- tested_spec[!tested_spec %in% declared_spec] + +spec_tests[["are_declared"]] <- sapply(spec_tests[["spec_id"]], function(x) all(x %in% declared_spec)) + +# Count tests in the different categories ---- +mask_failed <- !!spec_tests[["failed"]] | spec_tests[["error"]] +mask_skipped <- !!spec_tests[["skipped"]] +mask_declared <- spec_tests[["are_declared"]] +n_pass_dec <- sum(!mask_failed & !mask_skipped & mask_declared) +n_fail_dec <- sum(mask_failed & mask_declared) +n_skip_dec <- sum(mask_skipped & mask_declared) +n_uncov <- length(uncovered_spec) +n_undec <- sum(!mask_declared) + +render_spec_table <- function(t) { + t <- t[trac_matrix_col] + colnames(t) <- names(trac_matrix_col) + t <- t[order(t[["Spec ID"]]), ] + DT::datatable(t, options = list(dom = "ltp"), filter = list(position = "top")) +} + +data_frame_by_row <- function(colnames, data) { + n <- length(data) + n_cols <- length(colnames) + stopifnot(n %% n_cols == 0) + columns <- vector("list", length = n_cols) + for (i in 1:n_cols) columns[[i]] <- unlist(data[seq(i, n, n_cols)]) + do.call(data.frame, setNames(columns, colnames)) +} + +# Select columns to be included in the tables ---- +trac_matrix_col <- c("Spec ID" = "spec_id_paste", "Spec" = "spec_paste", "Test Desc" = "desc", "File" = "file") + +# Check that validation passes and set title ---- +VALIDATION_PASSED <- n_fail_dec == 0 && n_uncov == 0 && n_undec == 0 && n_uncov == 0 # nolint + +result_symbol <- if (VALIDATION_PASSED) "\U02705" else "\U274C" +title <- paste(result_symbol, params[["package"]], params[["version"]]) +``` + +## `r title` +Date: `r format(Sys.time(), "%Y-%b-%d %H:%M:%S")` + +The following document generates a report for R packages, to satisfy the criteria of a "Released" status under the **Non-GxP** project. The QC report contains the following information: + +- **Specifications (specs):** These can be attached to every test that the user adds. +- **Traceability matrix:** Contains test cases with passed, failed, or skipped expectations. +- **Uncovered or undeclared specs** +- **Session Info and System Configuration** + +::: {.infobox .warning} +Please be advised that the QC report generated for this module does not imply validation according to any other GxP criteria. +The QC report only satisfies our internally developed quality checks for non-GxP criteria. +For clinical reporting purposes, it is essential to note that any outputs generated using this module must be checked and verified within a validated system that adheres to the appropriate GxP guidelines. +::: + +---- +# Traceability matrix + +In this traceability matrix only those tests that point to an specification are included. + +Test cases can contain several expectations a test is considered: + + - **passed** if all expectations in the test pass. + + - **failed** if at least one expectation in the test fails. + + - **skipped** if at least one expectation in the test is skipped. + +A test can be both **failed** and **skipped**. + +## Summary + +```{r summary} +data_frame_by_row( + colnames = c("Spec Exists", "Test", "Count", "color"), + data = list( + "Yes", "Pass", n_pass_dec, "white", + "Yes", "Failed", n_fail_dec, if (n_fail_dec > 0) "red" else "green", + "Yes", "Skipped", n_skip_dec, if (n_skip_dec > 0) "red" else "green", + "Yes", "No Test", n_uncov, if (n_uncov > 0) "red" else "green", + "No", "NA", n_undec, if (n_undec > 0) "red" else "green" + ) +) |> + DT::datatable( + rownames = FALSE, + options = list(columnDefs = list(list(visible = FALSE, targets = c(3))), dom = "tp"), + filter = list(position = "top") + ) |> + DT::formatStyle( + c("Count"), + valueColumns = "color", + backgroundColor = DT::JS("value") + ) +``` + +## Passed tests + +```{r passed_test} +render_spec_table(spec_tests[!mask_failed & !mask_skipped & mask_declared, ]) +``` + +## Failed tests + +```{r failed_test} +render_spec_table(spec_tests[mask_failed & mask_declared, ]) +``` + +## Skipped tests + +```{r skipped_test} +render_spec_table(spec_tests[mask_skipped & mask_declared, ]) +``` + +## Uncovered specifications + +```{r uncovered_spec, echo=FALSE} +data.frame("Uncovered Specifications" = uncovered_spec) |> + DT::datatable( + options = list(dom = "ltp"), + filter = list(position = "top") + ) +``` + +## Undeclared specifications + +This should always be empty, as non existant specs are controlled during test execution. + +```{r undeclared_spec, echo=FALSE, results = "asis"} +render_spec_table(spec_tests[!mask_declared, ]) +``` + +# Session Info and System Configuration + +```{r system_conf} +devtools::session_info() +``` + +# List of specifications +```{r spec_list} +j <- vapply( + vdoc[["spec_id_list"]], + function(x) { + eval( + str2expression( + paste0("vdoc[[\"specs\"]]$", x) + ) + ) + }, + FUN.VALUE = character(1) +) |> + gsub("\n", "
", x = _, fixed = TRUE) + +data.frame(spec_id = names(j), spec = j) |> + DT::datatable( + rownames = FALSE, + options = list( + dom = "ltp" + ), + filter = list(position = "top"), + escape = FALSE + ) +``` diff --git a/man/cash-.pack_of_constants.Rd b/man/cash-.pack_of_constants.Rd new file mode 100644 index 0000000..0bb5f82 --- /dev/null +++ b/man/cash-.pack_of_constants.Rd @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/aaa_preface.R +\name{$.pack_of_constants} +\alias{$.pack_of_constants} +\title{Extract constant from pack} +\usage{ +\method{$}{pack_of_constants}(pack, name) +} +\arguments{ +\item{pack}{pack_of_constants} + +\item{name}{target constant + +This function differs from the base list extraction method in that it avoids partial matching of keys and throws +an error if the looked-for constant is not contained within the pack.} +} +\description{ +Extract constant from pack +} +\keyword{internal} diff --git a/man/create_ae_cm_plot.Rd b/man/create_ae_cm_plot.Rd new file mode 100644 index 0000000..4fd38e3 --- /dev/null +++ b/man/create_ae_cm_plot.Rd @@ -0,0 +1,30 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/create_plots.R +\name{create_ae_cm_plot} +\alias{create_ae_cm_plot} +\title{Function to create ae or cm plot} +\usage{ +create_ae_cm_plot( + data, + x_limits, + palette, + sl_info, + vline_vars, + vline_day_numbers, + ref_date +) +} +\arguments{ +\item{data}{Data frame containing the data for the plot} + +\item{palette}{Named vector that contains the colors that are used in the plot} + +\item{limits}{Vector that contains the limits of the plot} +} +\value{ +A ggplot2 object +} +\description{ +Function to create ae or cm plot +} +\keyword{internal} diff --git a/man/create_lb_vs_plot.Rd b/man/create_lb_vs_plot.Rd new file mode 100644 index 0000000..8cf6c1a --- /dev/null +++ b/man/create_lb_vs_plot.Rd @@ -0,0 +1,50 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/create_plots.R +\name{create_lb_vs_plot} +\alias{create_lb_vs_plot} +\title{Function to create lab or vital sign plot} +\usage{ +create_lb_vs_plot( + data, + date, + val, + low_limit, + high_limit, + param, + summary_stats, + x_limits, + palette, + sl_info, + vline_vars, + vline_day_numbers, + ref_date +) +} +\arguments{ +\item{data}{Data frame containing the data for the plot} + +\item{val}{Character name of the variable that contains analyze value} + +\item{low_limit}{Character name of the variable that contains the values of the low limit of the normal range} + +\item{high_limit}{Character name of the variable that contains the values of the high limit of the normal range} + +\item{summary_stats}{Character name of the variable that contains the values of the summary statistic} + +\item{lb_selected_params}{Vector containing the values of the selected parameters} + +\item{day}{Character name of the variable that contains the analyze day} + +\item{params}{Character name of the variable that contains the values of the analyze parameters} + +\item{analysis_indicator}{Character name of the variable that contains the values analysis indicator} + +\item{limits}{Vector that contains the limits of the plot} +} +\value{ +A ggplot2 object +} +\description{ +Function to create lab or vital sign plot +} +\keyword{internal} diff --git a/man/create_vlines.Rd b/man/create_vlines.Rd new file mode 100644 index 0000000..f68341c --- /dev/null +++ b/man/create_vlines.Rd @@ -0,0 +1,22 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/create_plots.R +\name{create_vlines} +\alias{create_vlines} +\title{Add vertical lines to plot} +\usage{ +create_vlines(plot, plot_data, vline_vars, vline_day_numbers) +} +\arguments{ +\item{plot}{A ggplot2 object} + +\item{plot_data}{Data of the plot} + +\item{vline_vars}{A list used to define the label and position of dashed lines in the plots} +} +\value{ +A ggplot2 object +} +\description{ +Add vertical lines to plot +} +\keyword{internal} diff --git a/man/explorer_app.Rd b/man/explorer_app.Rd new file mode 100644 index 0000000..42f7945 --- /dev/null +++ b/man/explorer_app.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/dressing_room.R +\name{explorer_app} +\alias{explorer_app} +\title{Interactive demo/configuration tool for \code{\link[=mod_patient_profile]{mod_patient_profile()}}} +\usage{ +explorer_app(datasets = NULL) +} +\arguments{ +\item{datasets}{\verb{[list(data.frame(n))]} (optional) Datasets available to the module. One of them should be a +demographic subject-level dataset and the rest should be visit-dependent datasets. If not provided, the UI offers a +file input selector that is functionally equivalent.} +} +\description{ +Launch an interactive configuration app for \code{\link[=mod_patient_profile]{mod_patient_profile()}}. This application guides the user through the +configuration of the module, offering an experimental point-and-click interface to the module API. Help is accessible +by hovering over any of the provided parameters. \cr +To try it using demo data, run \code{dv.papo::explorer_app(dv.papo:::prep_safety_data())} in your R prompt. +} diff --git a/man/figures/demo.png b/man/figures/demo.png new file mode 100644 index 0000000000000000000000000000000000000000..649ccbbe33aec71427b2ee8b7a318e5ae53c52f9 GIT binary patch literal 105707 zcmeFZ2UJwswk=wUf{EZ(Ohf@iQjtRuRa7MBoP`331y$s%2&f1sIb$G5&Y{SNl7o^n zA~_ZriumUO_dfglcmBQqw)bwkt-W^G(xBFwbIdtM=%bIZ7W{o> zhNeLL@#t{;GUn96SxTbEu!|UP#6kH3#XMH&;l-u!`wY6QPZ}q+@0RUX9a3-6c%YkG zC+RXbwM4|Q)6_)l(ViZ4?iWNy>vwClS4(#~?bScYZ>dfMS4d@(c1s;|dVHFmMij{tRNR&-`q<#VapQ9pq11{qeL3N^_9C}MSy5}lrD^;Ip7FvS z!u9hU?$MX|;r7F}`|E0k@t4QtZaPyNy>34lypN0^WPefrR*>IUWht!9NDjqvlUDy* zqo+pLZfw|=dO{vucAuM^R9ZV#;CV5k{7NxTXOYlsZ=Cf@v6k5N4dw$k_XRRh)bt`Q zwtEP%+dte8_O_=td8Eim-*%i~V%8&Lm1U1yuX%rQk56KQnMq%7e?ncH^j$&h+uC#V zu{pSWLgXvN(jDRY&z!>+Y?2F#A&wJFgD3&ThHj|L7s4r~ z>InT3+R5@?s9R}LCB@8q4e*&x>3yEj3w!Yrd*1)-s|(vwD}Fc1zuvh?R{zL@kbw8b 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z8uk_wq0XS^o#0qgML4+k^A@jOFzB3xb}|RciJMnEpRqzi_-v2R)Y;YdUU95zIP|<% zh)Q239g*_2{sjfANHOk|gsyM#mIgq#=8yeW0r=M4sfKh%>;kCfJv$1|W5L~pcl$fGN7m@2ZM<#N^all9q~L;AbV2atkVQePAvl(SAOG|H0|`J9{>MB3xE zsDhW#J8C(_RF)Mna7fM#UT6~LD^D!9r`Bu^y%7kj56?o&TVAzE-{oT2`nYxly@9SU zl_|O;hqbvl-Z+0tb01wIgmeS?y{Lwg+;EbR{$is#&ctLx3tLup^aB3FvI^WJgK0P{ zHJCbddXOFLC&)m#+}{>X-fAI(%v9K-8gJTFq221Ij{1@Zitv=UPL5w74E-zcxZH?> zamA@))wwMd_ae`xJz2d>4zQ$t%PdlB(@XHo<5YTQOZ!JX_u0T=***Cv_^Cz`1i=!B zMyWDN&0cYCD?hY+F!=5w!m}9>3aO-wdDv`AS8xnydi@(+gNYf3IkqP)FIFWy9?FgG zduabvMsMUxEwJW3&Ly28!RZaFr*EAIU(I~HQhBBtxwo&bY@d4%>Fv+o|IzMEitC#H@jSWQ~}UA$+bJj<^RUmg|Re SW5^Ds8{9OxQF86!^Zy1l$W{RW literal 0 HcmV?d00001 diff --git a/man/get_labels.Rd b/man/get_labels.Rd new file mode 100644 index 0000000..1e8b87d --- /dev/null +++ b/man/get_labels.Rd @@ -0,0 +1,25 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data_prep.R +\name{get_labels} +\alias{get_labels} +\title{This function will return corresponding labels in a dataset.} +\usage{ +get_labels(dataset, col_names = NULL, keep_as_original = FALSE) +} +\arguments{ +\item{dataset}{Dataset to get labels from.} + +\item{col_names}{Vector of character names of the columns in the dataset.} + +\item{keep_as_original}{Logical TRUE or FALSE: If TRUE, the corresponding column with +no label will return column name, else return NA. +If not assigned, it will return all labels of the the dataset. Otherwise, +only labels of corresponding columns will be returned.} +} +\value{ +Vector containing the labels of the dataset +} +\description{ +This function will return corresponding labels in a dataset. +} +\keyword{internal} diff --git a/man/mock_patient_profile_UI.Rd b/man/mock_patient_profile_UI.Rd new file mode 100644 index 0000000..59471eb --- /dev/null +++ b/man/mock_patient_profile_UI.Rd @@ -0,0 +1,18 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mock_patient_profile.R +\name{mock_patient_profile_UI} +\alias{mock_patient_profile_UI} +\title{Mock UI for papo module} +\usage{ +mock_patient_profile_UI(request) +} +\arguments{ +\item{id}{A unique identifier.} +} +\value{ +Shiny UI for the papomodule. +} +\description{ +Mock UI for papo module +} +\keyword{internal} diff --git a/man/mock_patient_profile_app.Rd b/man/mock_patient_profile_app.Rd new file mode 100644 index 0000000..038c27e --- /dev/null +++ b/man/mock_patient_profile_app.Rd @@ -0,0 +1,13 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mock_patient_profile.R +\name{mock_patient_profile_app} +\alias{mock_patient_profile_app} +\title{Run papo mock} +\usage{ +mock_patient_profile_app(auto_update_query_string = FALSE) +} +\description{ +\code{mock_patient_profile_app()} runs the \pkg{dv.papo} module +with dummy data. +} +\keyword{internal} diff --git a/man/mock_patient_profile_server.Rd b/man/mock_patient_profile_server.Rd new file mode 100644 index 0000000..5ef7cf2 --- /dev/null +++ b/man/mock_patient_profile_server.Rd @@ -0,0 +1,15 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mock_patient_profile.R +\name{mock_patient_profile_server} +\alias{mock_patient_profile_server} +\title{Mock server for papo module} +\usage{ +mock_patient_profile_server(input, output, session) +} +\arguments{ +\item{input, output, session}{Internal parameters for shiny.} +} +\description{ +Uses adsl, adae, and adcm data of roche dataset. +} +\keyword{internal} diff --git a/man/mock_with_mm_app.Rd b/man/mock_with_mm_app.Rd new file mode 100644 index 0000000..43bf4ef --- /dev/null +++ b/man/mock_with_mm_app.Rd @@ -0,0 +1,13 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mock_with_mm.R +\name{mock_with_mm_app} +\alias{mock_with_mm_app} +\title{Run an example for Patient profile integrated in the module manager} +\usage{ +mock_with_mm_app() +} +\description{ +Launches an example app that shows a patient profile module integrated in the +module manager surface. Displays data from the \pkg{safetyData} package. +} +\keyword{internal} diff --git a/man/mod_patient_profile.Rd b/man/mod_patient_profile.Rd new file mode 100644 index 0000000..cfb8573 --- /dev/null +++ b/man/mod_patient_profile.Rd @@ -0,0 +1,280 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_patient_profile.R +\name{mod_patient_profile} +\alias{mod_patient_profile} +\title{Patient Profile Module} +\usage{ +mod_patient_profile( + module_id = "", + subject_level_dataset_name = NULL, + subjid_var = NULL, + sender_ids = NULL, + summary = NULL, + listings = NULL, + plots = NULL +) +} +\arguments{ +\item{module_id}{\verb{[character]} +Unique Shiny module identifier.} + +\item{subject_level_dataset_name}{\verb{[character]} +Subject-level dataset name.} + +\item{subjid_var}{\verb{[character]} +Unique subject identifier column.} + +\item{sender_ids}{\verb{[character(n)]} (optional) +Identifiers of modules allowed to request the display of target patient IDs.} + +\item{summary}{\verb{[list]} (optional) +Subject-level summary section. +Composed of: +\itemize{ +\item vars +\verb{[character(n)]} +Values to display in the summary section. +Indexes into dataset \code{subject_level_dataset_name}. +\item column_count +\verb{[integer]} +Column count for the summary section. +}} + +\item{listings}{\verb{[list(n)]} (optional) +Listings section. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item default_vars +\verb{[character(n)]} (optional) +Default columns to display. If not specified, the first six columns are +selected by default. +Indexes into dataset \code{dataset}. +}} + +\item{plots}{\verb{[list]} (optional) +Plot section. +Composed of: +\itemize{ +\item timeline_info +\verb{[list]} +Start and end study dates. +Composed of: +\itemize{ +\item icf_date +\verb{[character]} (optional) +Informed Consent Form signing Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_start_date +\verb{[character]} +Treatment Start Date, used also as Day 1 Reference Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_end_date +\verb{[character]} +Treatment End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item part_end_date +\verb{[character]} (optional) +Participation End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +} +\item range_plots +\verb{[list(n)]} +Plots for range-like events (adverse events, concomitant medications, ...). +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the event. +Composed of: +\itemize{ +\item start_date +\verb{[character]} +Start date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item end_date +\verb{[character]} +End date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item decode +\verb{[character]} +Descriptive event label. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item grading +\verb{[character]} (optional) +Degree of the event, used for color-coding the plot. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item serious_ae +\verb{[character]} (optional) +Marker of event seriousness, usually reserved for adverse event datasets. +Indexes into dataset \code{dataset}. Expects \verb{[logical|"Y"/"N"]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over the left edge of each range. +The names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item value_plots +\verb{[list(n)]} +Plots for value-like (lab measurements, vital signs, ...) traces. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the trace. +Composed of: +\itemize{ +\item analysis_param +\verb{[character]} +Parameter. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item analysis_val +\verb{[character]} +Value. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item analysis_date +\verb{[character]} +Date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item analysis_indicator +\verb{[character]} (optional) +Analysis reference range indicator. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item range_low_limit +\verb{[character]} (optional) +Lower limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item range_high_limit +\verb{[character]} (optional) +Upper limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item summary_stats +\verb{[character]} (optional) +Additional value column for summary statistics. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over each point of the trace. The +names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item vline_vars +\verb{[character(n)]} +Place vertical dashed lines on days indicated by this dataset columns. +Indexes into dataset \code{subject_level_dataset_name}. Expects +\verb{[integer|Date|POSIXt]} values. +\item vline_day_numbers +\verb{[integer(n)]} (optional) +Place vertical dashed lines on days indicated by this parameter. +Represents a CDISC (non-zero) Study Day. +\item palette +\verb{[character(n)]} (optional) +If a name on this list matches the text on a plot element, the associated color +will be applied to that element. This mapping takes precedence over the +built-in palette. +Contains either an HTML (#xxxxxx) or an R color. +}} +} +\value{ +A list composed of the following elements: +\itemize{ +\item{\code{ui}}: Shiny UI function. +\item{\code{server}}: Shiny server function. +\item{\code{module_id}}: Shiny unique identifier. +} +} +\description{ +\code{mod_patient_profile} is a DaVinci Shiny module that displays patient information on a subject-level basis. It +consists of three sections: summary, listings and plots. +\itemize{ +\item The \code{summary} section shows visit-independent demographic information. +\item The \code{listings} section offers listings for visit-dependent information. +\item The \code{plots} section displays charts for events that happen over a span of time (adverse events, concomitant +medications, ...) or line plots of point-like events (laboratory values, vital sign measurements). +}\if{html}{\out{ +
+Show/hide usage example +
+
+What follows is a sample call to the mod_patient_profile function. +See the main article of this package for a tutorial on how to parameterize it. +
+dv.papo::mod_patient_profile(
+  module_id = "papo",
+  subject_level_dataset_name = "adsl",
+  subjid_var = "USUBJID",
+  summary = list(
+    vars = c("SUBJID", "SITEID", "ARM", "TRTSDT", "TRTEDT", "AGE", "RACE", "SEX", "BMIBL"),
+    column_count = 3L
+  ),
+  listings = list(
+    "Concomitant Medication" = list(
+      dataset = "cm"
+    ),
+    "Adverse Events" = list(
+      dataset = "adae",
+      default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV")
+    )
+  ),
+  plots = list(
+    timeline_info = c(trt_start_date = "TRTSDT", trt_end_date = "TRTEDT"),
+    range_plots = list(
+      "Concomitant Medication" = list(
+        dataset = "cm",
+        vars = c(
+          start_date = "CMSTDT", end_date = "CMENDT",
+          decode = "CMDECOD", grading = "CMDECOD"
+        ),
+        tooltip = c()
+      ),
+      "Adverse Events" = list(
+        dataset = "adae",
+        vars = c(
+          start_date = "ASTDT", end_date = "AENDT", decode = "AEDECOD",
+          grading = "AESEV", serious_ae = "AESER"
+        ),
+        tooltip = c("AE Start Day: " = "ASTDY", "AE End Day: " = "AENDY")
+      )
+    ),
+    value_plots = list(
+      "Lab Values" = list(
+        dataset = "lb",
+        vars = c(
+          analysis_param = "PARAM", analysis_val = "AVAL", analysis_date = "ADT",
+          analysis_indicator = "LBNRIND", range_low_limit = "A1LO", range_high_limit = "A1HI"
+        ),
+        tooltip = c()
+      )
+    ),
+    vline_vars = c(
+      "Informed Consent Date" = "RFICDT"
+    )
+  )
+)
+
+
+
+
+}} +} +\seealso{ +\code{\link[=mod_patient_profile_UI]{mod_patient_profile_UI()}}, \code{\link[=mod_patient_profile_server]{mod_patient_profile_server()}} +} diff --git a/man/mod_patient_profile_UI.Rd b/man/mod_patient_profile_UI.Rd new file mode 100644 index 0000000..6571d86 --- /dev/null +++ b/man/mod_patient_profile_UI.Rd @@ -0,0 +1,22 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_patient_profile.R +\name{mod_patient_profile_UI} +\alias{mod_patient_profile_UI} +\title{Patient Profile Module UI} +\usage{ +mod_patient_profile_UI(id) +} +\arguments{ +\item{id}{\verb{[character]} Unique shiny ID. Must match the ID provided to \code{\link[=mod_patient_profile_server]{mod_patient_profile_server()}}.} +} +\value{ +Shiny UI. +} +\description{ +(For use outside of the DaVinci framework)\cr +Places the Patient Profile module UI at the call site of this function. A matching call to \code{\link[=mod_patient_profile_server]{mod_patient_profile_server()}} +is necessary.\cr +} +\seealso{ +\code{\link[=mod_patient_profile]{mod_patient_profile()}} and \code{\link[=mod_patient_profile_server]{mod_patient_profile_server()}} +} diff --git a/man/mod_patient_profile_params.Rd b/man/mod_patient_profile_params.Rd new file mode 100644 index 0000000..fc1902e --- /dev/null +++ b/man/mod_patient_profile_params.Rd @@ -0,0 +1,202 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_signature.R +\name{mod_patient_profile_params} +\alias{mod_patient_profile_params} +\title{Dummy function to extract parameter documentation from mod_patient_profile_API} +\usage{ +mod_patient_profile_params( + module_id, + subject_level_dataset_name, + subjid_var, + sender_ids, + summary, + listings, + plots +) +} +\arguments{ +\item{module_id}{\verb{[character]} +Unique Shiny module identifier.} + +\item{subject_level_dataset_name}{\verb{[character]} +Subject-level dataset name.} + +\item{subjid_var}{\verb{[character]} +Unique subject identifier column.} + +\item{sender_ids}{\verb{[character(n)]} (optional) +Identifiers of modules allowed to request the display of target patient IDs.} + +\item{summary}{\verb{[list]} (optional) +Subject-level summary section. +Composed of: +\itemize{ +\item vars +\verb{[character(n)]} +Values to display in the summary section. +Indexes into dataset \code{subject_level_dataset_name}. +\item column_count +\verb{[integer]} +Column count for the summary section. +}} + +\item{listings}{\verb{[list(n)]} (optional) +Listings section. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item default_vars +\verb{[character(n)]} (optional) +Default columns to display. If not specified, the first six columns are +selected by default. +Indexes into dataset \code{dataset}. +}} + +\item{plots}{\verb{[list]} (optional) +Plot section. +Composed of: +\itemize{ +\item timeline_info +\verb{[list]} +Start and end study dates. +Composed of: +\itemize{ +\item icf_date +\verb{[character]} (optional) +Informed Consent Form signing Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_start_date +\verb{[character]} +Treatment Start Date, used also as Day 1 Reference Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_end_date +\verb{[character]} +Treatment End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item part_end_date +\verb{[character]} (optional) +Participation End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +} +\item range_plots +\verb{[list(n)]} +Plots for range-like events (adverse events, concomitant medications, ...). +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the event. +Composed of: +\itemize{ +\item start_date +\verb{[character]} +Start date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item end_date +\verb{[character]} +End date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item decode +\verb{[character]} +Descriptive event label. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item grading +\verb{[character]} (optional) +Degree of the event, used for color-coding the plot. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item serious_ae +\verb{[character]} (optional) +Marker of event seriousness, usually reserved for adverse event datasets. +Indexes into dataset \code{dataset}. Expects \verb{[logical|"Y"/"N"]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over the left edge of each range. +The names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item value_plots +\verb{[list(n)]} +Plots for value-like (lab measurements, vital signs, ...) traces. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the trace. +Composed of: +\itemize{ +\item analysis_param +\verb{[character]} +Parameter. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item analysis_val +\verb{[character]} +Value. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item analysis_date +\verb{[character]} +Date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item analysis_indicator +\verb{[character]} (optional) +Analysis reference range indicator. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item range_low_limit +\verb{[character]} (optional) +Lower limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item range_high_limit +\verb{[character]} (optional) +Upper limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item summary_stats +\verb{[character]} (optional) +Additional value column for summary statistics. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over each point of the trace. The +names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item vline_vars +\verb{[character(n)]} +Place vertical dashed lines on days indicated by this dataset columns. +Indexes into dataset \code{subject_level_dataset_name}. Expects +\verb{[integer|Date|POSIXt]} values. +\item vline_day_numbers +\verb{[integer(n)]} (optional) +Place vertical dashed lines on days indicated by this parameter. +Represents a CDISC (non-zero) Study Day. +\item palette +\verb{[character(n)]} (optional) +If a name on this list matches the text on a plot element, the associated color +will be applied to that element. This mapping takes precedence over the +built-in palette. +Contains either an HTML (#xxxxxx) or an R color. +}} +} +\value{ +No return value. +} +\description{ +Generated by \code{write_mod_param_help.R}. +} +\keyword{internal} diff --git a/man/mod_patient_profile_server.Rd b/man/mod_patient_profile_server.Rd new file mode 100644 index 0000000..33ea6fe --- /dev/null +++ b/man/mod_patient_profile_server.Rd @@ -0,0 +1,204 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_patient_profile.R +\name{mod_patient_profile_server} +\alias{mod_patient_profile_server} +\title{Patient Profile Module server} +\usage{ +mod_patient_profile_server( + id, + subject_level_dataset, + extra_datasets, + subjid_var, + sender_ids, + summary, + listings, + plots +) +} +\arguments{ +\item{id}{\verb{[character]} Unique shiny ID. Must match the ID provided to \code{\link[=mod_patient_profile_UI]{mod_patient_profile_UI()}}.} + +\item{subject_level_dataset}{\verb{[reactive(data.frame)]} Visit-independent subject information.} + +\item{extra_datasets}{\verb{[reactive(data.frame(n))]} Visit-dependent subject datasets.} + +\item{subjid_var}{\verb{[character]} +Unique subject identifier column.} + +\item{sender_ids}{\verb{[character(n)]} (optional) +Identifiers of modules allowed to request the display of target patient IDs.} + +\item{summary}{\verb{[list]} (optional) +Subject-level summary section. +Composed of: +\itemize{ +\item vars +\verb{[character(n)]} +Values to display in the summary section. +Indexes into dataset \code{subject_level_dataset_name}. +\item column_count +\verb{[integer]} +Column count for the summary section. +}} + +\item{listings}{\verb{[list(n)]} (optional) +Listings section. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item default_vars +\verb{[character(n)]} (optional) +Default columns to display. If not specified, the first six columns are +selected by default. +Indexes into dataset \code{dataset}. +}} + +\item{plots}{\verb{[list]} (optional) +Plot section. +Composed of: +\itemize{ +\item timeline_info +\verb{[list]} +Start and end study dates. +Composed of: +\itemize{ +\item icf_date +\verb{[character]} (optional) +Informed Consent Form signing Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_start_date +\verb{[character]} +Treatment Start Date, used also as Day 1 Reference Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item trt_end_date +\verb{[character]} +Treatment End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +\item part_end_date +\verb{[character]} (optional) +Participation End Date. +Indexes into dataset \code{subject_level_dataset_name}. Expects \verb{[Date|POSIXt]} +values. +} +\item range_plots +\verb{[list(n)]} +Plots for range-like events (adverse events, concomitant medications, ...). +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the event. +Composed of: +\itemize{ +\item start_date +\verb{[character]} +Start date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item end_date +\verb{[character]} +End date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item decode +\verb{[character]} +Descriptive event label. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item grading +\verb{[character]} (optional) +Degree of the event, used for color-coding the plot. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item serious_ae +\verb{[character]} (optional) +Marker of event seriousness, usually reserved for adverse event datasets. +Indexes into dataset \code{dataset}. Expects \verb{[logical|"Y"/"N"]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over the left edge of each range. +The names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item value_plots +\verb{[list(n)]} +Plots for value-like (lab measurements, vital signs, ...) traces. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item vars +\verb{[list]} +Variables of interest for the trace. +Composed of: +\itemize{ +\item analysis_param +\verb{[character]} +Parameter. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item analysis_val +\verb{[character]} +Value. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item analysis_date +\verb{[character]} +Date. +Indexes into dataset \code{dataset}. Expects \verb{[Date|POSIXt]} values. +\item analysis_indicator +\verb{[character]} (optional) +Analysis reference range indicator. +Indexes into dataset \code{dataset}. Expects \verb{[character|factor]} values. +\item range_low_limit +\verb{[character]} (optional) +Lower limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item range_high_limit +\verb{[character]} (optional) +Upper limit of the reference range. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +\item summary_stats +\verb{[character]} (optional) +Additional value column for summary statistics. +Indexes into dataset \code{dataset}. Expects \verb{[numeric]} values. +} +\item tooltip +\verb{[character(n)]} +Block of text to display as hover information over each point of the trace. The +names of this list are included as literal text and honor three basic HTML +formatting elements: \verb{}, \verb{}, \verb{
}). The columns the values refer to are +populated with the value on the dataset relevant to any given row. +Indexes into dataset \code{dataset}. +} +\item vline_vars +\verb{[character(n)]} +Place vertical dashed lines on days indicated by this dataset columns. +Indexes into dataset \code{subject_level_dataset_name}. Expects +\verb{[integer|Date|POSIXt]} values. +\item vline_day_numbers +\verb{[integer(n)]} (optional) +Place vertical dashed lines on days indicated by this parameter. +Represents a CDISC (non-zero) Study Day. +\item palette +\verb{[character(n)]} (optional) +If a name on this list matches the text on a plot element, the associated color +will be applied to that element. This mapping takes precedence over the +built-in palette. +Contains either an HTML (#xxxxxx) or an R color. +}} +} +\description{ +(For use outside of the DaVinci framework)\cr +Runs the server that populates the UI returned by \code{\link[=mod_patient_profile_UI]{mod_patient_profile_UI()}}.\cr +Requires a matching call to that function. +} +\seealso{ +\code{\link[=mod_patient_profile]{mod_patient_profile()}} and \code{\link[=mod_patient_profile_UI]{mod_patient_profile_UI()}} +} diff --git a/man/pack_of_constants.Rd b/man/pack_of_constants.Rd new file mode 100644 index 0000000..1db999e --- /dev/null +++ b/man/pack_of_constants.Rd @@ -0,0 +1,46 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/aaa_preface.R +\name{pack_of_constants} +\alias{pack_of_constants} +\title{Build a collection of named constants} +\usage{ +pack_of_constants(...) +} +\arguments{ +\item{...}{Named parameters to be collected as constants} +} +\description{ +Build a collection of named constants +} +\details{ +Shiny uses strings as IDs to link UI and server elements. E.g: +foo_UI(id = ns("foo")) ... +foo_server(id = "foo") + +This pattern makes it easy for programmers to fall on the trap of modifying one instance of the string literal "foo" +without modifying the rest and be unaware of the problem until a bug is hit. It's also easy to mistakes uses of "foo" +as an identifier from other uses (text labels, ...) when, as it's often the case, the parameter is not explicitly +named. +One easy fix consists in using global variables instead of plain string literals. In the case of the previous +example, that would mean: +ID_FOO <- "foo" +foo_UI(ns(ID_FOO)) ... +foo_server(ID_FOO) + +That simple addition makes the purpose of ID_FOO clear and also fails gracefully when not all ID_FOO instances are +updated synchronously along a codebase. It has the drawback of polluting the global namespace with identifier +variables. That's easily solved by creating a container of constants, which is the purpose of this pack_of_constants +alias. +ID <- pack_of_constants(FOO = "foo", BAR = "bar") +ID$FOO +"foo" +ID$BA +Error in \verb{$.pack_of_constants}(ID, BA) : +Pack of constants "ID" does not contain "BA" + +The pack of constants is a plain named list that enforces that all elements have unique, non-null names. +It is tagged as an S3 object to override its extraction operators. + +The use of checkmate is unnecessary, but it's a Good Library(TM) and your module should rely on it anyways +} +\keyword{internal} diff --git a/man/patient_info_UI.Rd b/man/patient_info_UI.Rd new file mode 100644 index 0000000..37ce18f --- /dev/null +++ b/man/patient_info_UI.Rd @@ -0,0 +1,19 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_patient_info.R +\name{patient_info_UI} +\alias{patient_info_UI} +\title{Create user interface for the patient information shiny module of \pkg{dv.papo}} +\usage{ +patient_info_UI(id) +} +\arguments{ +\item{id}{A unique ID string to create a namespace. Must match the ID of +\code{patient_info_server()}.} +} +\value{ +A shiny \code{uiOutput} element. +} +\description{ +Create user interface for the patient information shiny module of \pkg{dv.papo} +} +\keyword{internal} diff --git a/man/patient_info_server.Rd b/man/patient_info_server.Rd new file mode 100644 index 0000000..da3a093 --- /dev/null +++ b/man/patient_info_server.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_patient_info.R +\name{patient_info_server} +\alias{patient_info_server} +\title{Create server for the patient information shiny module of \pkg{dv.papo}} +\usage{ +patient_info_server(id, record, subjid_var, column_count = 3) +} +\arguments{ +\item{id}{A unique ID string to create a namespace. Must match the ID of +\code{patient_info_UI()}.} + +\item{record}{row object of dataframe: row record for patient.} + +\item{subjid_var}{\verb{[character]} +Unique subject identifier column.} + +\item{column_count}{A number indicating how many items should be in one row} +} +\description{ +Create server for the patient information shiny module of \pkg{dv.papo} +} +\keyword{internal} diff --git a/man/patient_listing_UI.Rd b/man/patient_listing_UI.Rd new file mode 100644 index 0000000..beb1e5e --- /dev/null +++ b/man/patient_listing_UI.Rd @@ -0,0 +1,16 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_listing.R +\name{patient_listing_UI} +\alias{patient_listing_UI} +\title{Create user interface for patient listings shiny module of \pkg{dv.papo}} +\usage{ +patient_listing_UI(id) +} +\arguments{ +\item{id}{A unique ID string to create a namespace. Must match the ID of +\code{patient_plot_server()}.} +} +\description{ +Create user interface for patient listings shiny module of \pkg{dv.papo} +} +\keyword{internal} diff --git a/man/patient_listing_server.Rd b/man/patient_listing_server.Rd new file mode 100644 index 0000000..8833e2d --- /dev/null +++ b/man/patient_listing_server.Rd @@ -0,0 +1,34 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_listing.R +\name{patient_listing_server} +\alias{patient_listing_server} +\title{Create server for patient listings shiny module of \pkg{dv.papo}} +\usage{ +patient_listing_server(id, data_list, key_value, listings) +} +\arguments{ +\item{id}{A unique ID string to create a namespace. Must match the ID of +\code{patient_listing_UI()}.} + +\item{data_list}{List of data frames containing data for each listing of selected patient.} + +\item{key_value}{Character: Value of selected patient} + +\item{listings}{\verb{[list(n)]} (optional) +Listings section. +Composed of: +\itemize{ +\item dataset +\verb{[character]} +Dataset name. +\item default_vars +\verb{[character(n)]} (optional) +Default columns to display. If not specified, the first six columns are +selected by default. +Indexes into dataset \code{dataset}. +}} +} +\description{ +Create server for patient listings shiny module of \pkg{dv.papo} +} +\keyword{internal} diff --git a/man/patient_plot_UI.Rd b/man/patient_plot_UI.Rd new file mode 100644 index 0000000..4ccbbcc --- /dev/null +++ b/man/patient_plot_UI.Rd @@ -0,0 +1,18 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_plots.R +\name{patient_plot_UI} +\alias{patient_plot_UI} +\title{Create user interface for patient plot shiny module of \pkg{dv.papo}} +\usage{ +patient_plot_UI(id) +} +\arguments{ +\item{id}{A unique ID string to create a namespace. Must match the ID of +\code{patient_plot_server()}.} + +\item{title}{character: Title of plot module} +} +\description{ +Create user interface for patient plot shiny module of \pkg{dv.papo} +} +\keyword{internal} diff --git a/man/patient_plot_server.Rd b/man/patient_plot_server.Rd new file mode 100644 index 0000000..3edd36d --- /dev/null +++ b/man/patient_plot_server.Rd @@ -0,0 +1,23 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/mod_plots.R +\name{patient_plot_server} +\alias{patient_plot_server} +\title{Create server for patient plot shiny module of \pkg{dv.papo}} +\usage{ +patient_plot_server( + id, + subject_var, + subject_level_dataset, + timeline_info, + extra_datasets, + range_plots, + value_plots, + vline_vars, + vline_day_numbers, + palette +) +} +\description{ +TODO: Document params (inherit them) +} +\keyword{internal} diff --git a/man/prep_safety_data.Rd b/man/prep_safety_data.Rd new file mode 100644 index 0000000..50a58c4 --- /dev/null +++ b/man/prep_safety_data.Rd @@ -0,0 +1,20 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/prep_safety_data.R +\name{prep_safety_data} +\alias{prep_safety_data} +\title{Prepare safety data} +\usage{ +prep_safety_data(n = 200) +} +\arguments{ +\item{n}{Number of rows to select from the adsl dataset. The first n rows will be +taken. Used to reduce runtime during development.} +} +\value{ +A list of three data frames. +} +\description{ +Modifiy safetyData's adsl, adae, and adcm dummy data for easy use within +\pkg{dv.clinlines}. +} +\keyword{internal} diff --git a/man/pt_info_data_filter.Rd b/man/pt_info_data_filter.Rd new file mode 100644 index 0000000..d2f80de --- /dev/null +++ b/man/pt_info_data_filter.Rd @@ -0,0 +1,25 @@ +% Generated by roxygen2: do not edit by hand +% Please edit documentation in R/data_prep.R +\name{pt_info_data_filter} +\alias{pt_info_data_filter} +\title{Filter datasets for patient information section} +\usage{ +pt_info_data_filter(df, subjid_var, columns, selected_key) +} +\arguments{ +\item{df}{TODO} + +\item{subjid_var}{\verb{[character]} +Unique subject identifier column.} + +\item{columns}{TODO} + +\item{selected_key}{TODO} +} +\value{ +A list containing datasets for patient information and plots +} +\description{ +Filter datasets for patient information section +} +\keyword{internal} diff --git a/tests/testthat.R b/tests/testthat.R new file mode 100644 index 0000000..75e5719 --- /dev/null +++ b/tests/testthat.R @@ -0,0 +1,6 @@ +pkg_name <- "dv.papo" + +library(testthat) +library(pkg_name, character.only = TRUE) + +test_check(pkg_name) diff --git a/tests/testthat/apps/misconfigured_app/app.R b/tests/testthat/apps/misconfigured_app/app.R new file mode 100644 index 0000000..c6fac26 --- /dev/null +++ b/tests/testthat/apps/misconfigured_app/app.R @@ -0,0 +1,9 @@ +dataset_list <- list( + "demo" = dv.papo:::prep_safety_data(5) +) + +dv.manager::run_app( + data = dataset_list, + module_list = list("Papo" = dv.papo::mod_patient_profile(module_id = "papo")), + filter_data = "adsl" +) diff --git a/tests/testthat/apps/patient_selector_switching/app.R b/tests/testthat/apps/patient_selector_switching/app.R new file mode 100644 index 0000000..892a0cc --- /dev/null +++ b/tests/testthat/apps/patient_selector_switching/app.R @@ -0,0 +1,129 @@ +dataset_list <- list( + "demo" = dv.papo:::prep_safety_data(5), + "demo2" = dv.papo:::prep_safety_data(10) +) + +module_list <- list( + "Papo" = dv.papo::mod_patient_profile( + module_id = "mock_app", + subjid_var = "USUBJID", + sender_ids = NULL, + subject_level_dataset_name = "adsl", + summary = list( + vars = c( + "SITEID", + "AGE", + "SEX", + "RACE", + "ETHNIC", + "ARM", + "DCREASCD", + "TRT01A" + ), + column_count = 3 + ), + listings = list( + "Adverse Event" = list(dataset = "adae", default_vars = NULL), + "Concomitant Medication" = list(dataset = "cm", default_vars = NULL) + ), + plots = list( + timeline_info = c( + trt_start_date = "TRTSDT", + trt_end_date = "TRTEDT", + icf_date = "RFICDT", + part_end_date = "RFENDT" + ), + vline_vars = c( + "Informed Consent Date" = "RFICDT", + "Study Treatment Stop Date" = "TRTEDT" + ), + vline_day_numbers = c( + "Study Treatment Start Day : Day 1" = 1 + ), + range_plots = list( + "Adverse Events Plot" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", + end_date = "AENDT", + decode = "AEDECOD", + grading = "AESEV", + serious_ae = "AESER" + ), + tooltip = c( + "AE Term: " = "AEDECOD", + "AE Reported Term: " = "AETERM", + "Primary SOC: " = "AESOC", + "Serious Event: " = "AESER", + "
AE Start Date: " = "ASTDT", + "AE Stop Date: " = "AENDT" + ) + ), + "Concomitant Medication Plot" = list( + dataset = "cm", + vars = c( + start_date = "CMSTDT", + end_date = "CMENDT", + decode = "CMDECOD", + grading = "CMINDC" + ), + tooltip = c( + "Standardized Medication Name: " = "CMDECOD", + "Indication: " = "CMINDC", + "
CM Dose: " = "CMDOSE", + "CM Dose Unit: " = "CMDOSU", + "
CM START Date: " = "CMSTDTC", + "CM End Date: " = "CMENDTC", + "CM START Day: " = "CMSTDY", + "CM END Day: " = "CMENDY" + ) + ) + ), + value_plots = list( + "Lab plot" = list( + dataset = "lb", + vars = c( + analysis_date = "ADT", + analysis_val = "AVAL", + analysis_param = "PARAM", + analysis_indicator = "ANRIND", + range_low_limit = "A1LO", + range_high_limit = "A1HI" + ), + tooltip = c( + "Lab Parameter: " = "PARAM", + "Lab Test Date: " = "ADT", + "Lab Test Visit :" = "AVISIT", + "
High Limit: " = "A1HI", + "Lab Standard Value: " = "AVAL", + "Lower Limit: " = "A1LO", + "
Analysis Indicator: " = "ANRIND" + ) + ), + "Vital Sign Plot" = list( + dataset = "vs", + vars = c( + analysis_date = "ADT", + analysis_val = "AVAL", + analysis_param = "PARAM", + analysis_indicator = "AVISIT", + summary_stats = "AVAL_MEAN" + ), + tooltip = c( + "Vital sign Parameter: " = "PARAM", + "Vital sign Date: " = "ADT", + "Vital sign Visit: " = "VISIT", + "
Vital sign Value: " = "AVAL", + "Vital sign mean value by visits: " = "AVAL_MEAN" + ) + ) + ) + ) + ) +) + +dv.manager::run_app( + data = dataset_list, + module_list = module_list, + filter_data = "adsl" +) diff --git a/tests/testthat/apps/root/app.R b/tests/testthat/apps/root/app.R new file mode 100644 index 0000000..b6f6106 --- /dev/null +++ b/tests/testthat/apps/root/app.R @@ -0,0 +1,19 @@ + +# TODO(miguel): Avoid having to install the package when testing locally by following +# dv.biomarker.general/browse/tests/testthat/app/app.R?at=dev +# to run the current version of the code + +# wrapper around mock_patient_profile_app that updates URL to reflect state of inputs +shiny::shinyApp( + ui = dv.papo::mock_patient_profile_UI, + server = function(input, output, session) { + dv.papo::mock_patient_profile_server(input, output, session) + + shiny::observe({ + shiny::reactiveValuesToList(input) + session$doBookmark() + }) + shiny::onBookmarked(shiny::updateQueryString) + }, + enableBookmarking = "url" +) diff --git a/tests/testthat/setup.R b/tests/testthat/setup.R new file mode 100644 index 0000000..7ca6d2e --- /dev/null +++ b/tests/testthat/setup.R @@ -0,0 +1,177 @@ +is_CI <- isTRUE(as.logical(Sys.getenv("CI"))) + +wait_for_idle_ms <- 1500 # Cope with slow tests + +# validation (S) +vdoc <- local({ + # ########## + # package_name is used # INSIDE # the sourced file below + # ########## + package_name <- "dv.papo" # hardcoded because devtools::check appears to use a different working directory + utils_file_path <- system.file("validation", "utils-validation.R", package = package_name, mustWork = TRUE) + source(utils_file_path, local = TRUE)[["value"]] +}) +specs <- vdoc[["specs"]] +# validation (F) + +# data & params setup + +# params set up +summary <- list( + vars = c( + "USUBJID", + "SITEID", + "AGE", + "SEX", + "RACE", + "ETHNIC", + "ARM", + "DCREASCD", + "TRT01A" + ), + column_count = 3 +) + +listings <- list( + "Adverse Events" = list( + dataset = "adae", + default_vars = c("USUBJID", "AETERM", "AEDECOD", "AESTDTC", "AEENDTC") + ), + "Concomitant Medication" = list( + dataset = "cm", + default_vars = c("USUBJID", "CMDECOD", "CMDOSE", "CMSTDTC", "CMENDTC") + ) +) + +timeline_info <- c( + trt_start_date = "TRTSDT", + trt_end_date = "TRTEDT", + icf_date = "RFICDT", + part_end_date = "RFENDT" +) + +vline_vars <- list( + "Informed Consent Day" = "RFICDT", + "Study Treatment Stop Day" = "TRTEDT" +) + +range_plots <- list( + "Adverse Events Plot" = list( + dataset = "adae", + vars = c( + start_day = "AESTDY", + end_day = "AEENDY", + decode = "AEDECOD", + grading = "AESEV", + serious_ae = "AESER" + ), + tooltip = c( + ## we have to think about how we can make it simpler + "AE Term: " = "AEDECOD", + "AE Reported Term:" = "AETERM", + "Primary SOC: " = "AESOC", + "Intensity: " = "ASEV", + "Serious Event: " = "AESER", + "add_break" = "", + "Treatment Start Date: " = "TRTSDT", + "Treatment Stop Date: " = "TRTEDT", + "add_break" = "", + "AE Start Date: " = "AESTDTC", + "AE Stop Date: " = "AEENDTC", + "AE Start Day: " = "AESTDY", + "AE Stop Day: " = "AEENDY", + "add_break" = "", + "CM or add. Treatment: " = "ACONTRT", + "Action Taken with Study Treatment: " = "AACN", + "Drug Related: " = "AREL", + "Comment for Discont of Treatment: " = "DCTREAS", + "DLT Indicator: " = "ADLT" + ) + ), + "Concomitant Medication Plot" = list( + dataset = "cm", + vars = c( + start_day = "CMSTDY", + end_day = "CMENDY", + decode = "CMDECOD", + grading = "CMINDC" + ), + tooltip = c( + "Standardized Medication Name: " = "CMDECOD", + "Indication: " = "CMINDC", + "Indication Term: " = "CMINDC0", + "add_break" = "", + "CM Dose: " = "CMDOSE", + "CM Dose Unit: " = "CMDOSU", + "add_break" = "", + "Treatment Start Date: " = "TRTSDT", + "Treatment Stop Date: " = "TRTEDT", + "add_break" = "", + "CM START Date: " = "CMSTDTC", + "CM End Date: " = "CMENDTC", + "CM START Day: " = "CMSTDY", + "CM END Day: " = "CMENDY", + "CM START Date Imputation Flag: " = "ASTDTF", + "CM End Date Imputation Flag: " = "AENDTF", + "add_break" = "", + "Planned Sequence of Treatments: " = "TRTSEQP", + "Actual Sequence of Treatments: " = "TRTSEQA" + ) + ) +) + +value_plots <- list( + "Lab plot" = list( + dataset = "lb", + vars = c( + analysis_day = "LBDY", + analysis_val = "LBORRES", + analysis_param = "LBTEST", + analysis_indicator = "LBNRIND", + range_low_limit = "LBORNRLO", + range_high_limit = "LBORNRHI" + ), + tooltip = c( + "Lab Parameter: " = "LBTEST", + "Lab Test Day: " = "LBDY", + "Lab Test Visit :" = "VISIT", + "add_break" = "", + "High Limit: " = "LBSTNRHI", + "Lab Standard Value: " = "LBORRES", + "Lower Limit: " = "LBSTNRLO", + "add_break" = "", + "Analysis Indicator: " = "LBNRIND" + ) + ), + "Vital Sign Plot" = list( + dataset = "vs", + vars = c( + analysis_day = "VSDY", + analysis_val = "VSORRES", + analysis_param = "VSTEST", + analysis_indicator = "VISIT", + range_low_limit = NULL, + range_high_limit = NULL, + summary_stats = "AVAL_MEAN" + ), + tooltip = c( + "Vital sign Parameter: " = "VSTEST", + "Vital sign Day: " = "VSDY", + "Vital sign Visit: " = "VISIT", + "add_break" = "", + "Vital sign Value: " = "VSORRES", + "Vital sign mean value by visits: " = "AVAL_MEAN" + ) + ) +) + +# data +testd1 <- dv.papo:::prep_safety_data(5) +testd1_sl <- testd1[["adsl"]] +testd1_extra <- testd1[setdiff(names(testd1), "adsl")] +rm(testd1) + +root_app <- shinytest2::AppDriver$new(app_dir = "apps/root/") +root_app_url <- root_app$get_url() + +withr::defer(root_app$stop(), teardown_env()) diff --git a/tests/testthat/test-all.R b/tests/testthat/test-all.R new file mode 100644 index 0000000..9e0c2dc --- /dev/null +++ b/tests/testthat/test-all.R @@ -0,0 +1,350 @@ +test_that( + "functional subject_selector" |> + vdoc[["add_spec"]](c(specs$common$subject_selector)), + { + test_pid <- "01-701-1028" + test_tab <- "cm" + + shiny::testServer(mod_patient_profile_server, args = list( + id = "test", + subject_level_dataset = shiny::reactive(testd1_sl), + extra_datasets = shiny::reactive(testd1_extra), + subjid_var = "USUBJID", + sender_ids = c(reactive(list("subj_id" = reactive("test")))), + summary = summary, + listings = listings, + plots = list( + timeline_info = timeline_info, + vline_vars = vline_vars, + range_plots = range_plots, + value_plots = value_plots, + palette = NULL + ) + ), { + session$setInputs(patient_selector = test_pid) + session$flushReact() + expect_equal( + filtered_pt_info_data() |> + select_columns_by_name("USUBJID") |> + unlist(use.names = FALSE), + test_pid + ) + }) + } +) + +test_that( + "functional bookmarking" |> + vdoc[["add_spec"]](c(specs$common$bookmarking)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(wait_for_idle_ms) + + sel_id <- "papo-patient_selector" + + inputs <- list() + inputs[[sel_id]] <- "01-701-1028" + + do.call(app$set_inputs, inputs) + app$wait_for_idle(wait_for_idle_ms) + + bmk_url <- app$get_js("window.location.href") + + bookmark_app <- shinytest2::AppDriver$new(bmk_url) + bookmark_app$wait_for_idle(wait_for_idle_ms) + app_input_values <- app$get_values()[["input"]] + bmk_input_values <- bookmark_app$get_values()[["input"]] + + expect_equal(app_input_values[[sel_id]], bmk_input_values[[sel_id]]) + app$stop() + } +) + +test_that( + "functional jump-to-subject" |> + vdoc[["add_spec"]](c(specs$common$jump_to_subject)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(wait_for_idle_ms) + app$click(input = "jump") + app$wait_for_idle(wait_for_idle_ms) + expected <- "01-701-1033" + actual <- app$get_value(input = "papo-patient_selector") + expect_equal(actual, expected) + app$stop() + } +) + +test_that( + "helpful configuration feedback" |> + vdoc[["add_spec"]](c(specs$common$misconfiguration_feedback)), + { + app <- shinytest2::AppDriver$new( + app_dir = "apps/misconfigured_app/", + name = "misconfigured_app" + ) + + app$wait_for_idle(wait_for_idle_ms) + + validation_errors <- app$get_html(selector = "#papo-validator-ui") + expect_true(grepl("`subject_level_dataset_name` missing", validation_errors, fixed = TRUE)) + expect_true(grepl("`subjid_var` missing", validation_errors, fixed = TRUE)) + + app$stop() + } +) + +test_that( + "patient selector updates after dataset change" |> + vdoc[["add_spec"]](c(specs$common$dataset_change)), + { + app <- shinytest2::AppDriver$new( + app_dir = "apps/patient_selector_switching/", + name = "patient_selector_switching" + ) + + app$set_inputs(`global_filter-vars` = "SEX") + app$wait_for_idle() + + # Check if the first patient was selected (initial state) + testthat::expect_equal(app$get_text("#mock_app-patient_selector"), "01-701-1015") + + # Check if the first male patient was selected when filtered accordingly + app$set_inputs(`global_filter-SEX` = "M") + # assign pat_id only to suppress print + pat_id <- app$wait_for_value(input = "mock_app-patient_selector", ignore = list("01-701-1015")) + testthat::expect_equal(app$get_text("#mock_app-patient_selector"), "01-701-1023") + + # Check if no patient is selected when filtered accordingly + app$set_inputs(`global_filter-SEX` = character(0)) + app$wait_for_idle(2000) + testthat::expect_equal(app$get_text("#mock_app-patient_selector"), "") + + app$stop() + } +) + +column_count_tst <- 4 +records <- testd1_sl %>% dplyr::filter(USUBJID == "01-701-1015") + +test_that( + "Subject level information will be shown in patient information section, + the total number and content of elements is customizable. The default number + of elements in one row is also customizable." |> + vdoc[["add_spec"]](c(specs$summary$columns)), + { + shiny::testServer( + patient_info_server, + arg = list( + id = "test", + record = reactive(records), + subjid_var = "USUBJID", + column_count = column_count_tst + ), + { + session$setInputs(patient_selector = "01-701-1023") + div_class <- paste0("col-sm-", 12 / column_count_tst) + + # check if the number of items equals to number of data columns, and + # if the div class is correct to ensure the number of items per + # is as expected + expect_equal( + length(gregexpr(div_class, output$ui_out$html, fixed = TRUE)[[1]]), + ncol(records) + ) + } + ) + } +) + +test_that( + "Column labels are shown as names in data listings if present" |> + vdoc[["add_spec"]](c(specs$listings$column_labels)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(wait_for_idle_ms) + app$set_inputs("papo-listings-column_selector_adae" = c("USUBJID")) + app$wait_for_idle(wait_for_idle_ms) + + selected_data <- app$get_values()[["export"]][["papo-listings-test_data"]][["filtered_data"]] + expect_equal(attr(selected_data[["USUBJID"]], "label"), "Unique Subject Identifier") + + app$stop() + } +) + +test_that( + "Tab controls allow listing switching" |> + vdoc[["add_spec"]](c(specs$listings$switching, specs$listings$extra_column_selection)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(duration = wait_for_idle_ms) + app$set_inputs("papo-listings-data_selector" = "cm") + app$wait_for_idle() + + target_columns <- c("USUBJID", "CMTRT") + app$set_inputs("papo-listings-column_selector_cm" = target_columns) + app$wait_for_idle() + + selected_data <- app$get_values()[["export"]][["papo-listings-test_data"]][["filtered_data"]] + testthat::expect_equal(names(selected_data), target_columns) + testthat::expect_equal(unique(selected_data[["USUBJID"]]), "01-701-1015") + testthat::expect_equal( + unique(selected_data[["CMTRT"]]), + c("ASPIRIN", "CALCIUM", "HYDROCORTISONE", "NEOSPORIN /USA/", "PREMARIN", "TYLENOL") + ) + app$stop() + } +) + +test_that( + "The content of data listing can be filtered by inputing related text in the + search box on the top right of the listing. It can also be filtered for each + column by inputing/selecting values from the text box below the column + header." |> + vdoc[["add_spec"]](c(specs$listings$filtering, specs$listings$sorting)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(1500) + app$set_inputs("papo-listings-data_selector" = "cm") + app$wait_for_idle(1500) + + target_columns <- c("USUBJID", "CMTRT") + app$set_inputs("papo-listings-column_selector_cm" = target_columns) + app$wait_for_idle(1500) + + listing_properties <- jsonlite::fromJSON(app$get_values()[["output"]][["papo-listings-listing"]])[["x"]] + + testthat::expect_equal(listing_properties[["filter"]], "top") + testthat::expect_equal(listing_properties[["options"]][["searching"]], TRUE) + testthat::expect_equal(listing_properties[["options"]][["ordering"]], TRUE) + testthat::expect_equal(listing_properties[["options"]][["buttons"]][["text"]], "Reset Columns Order") + + filter_html <- listing_properties[["filterHTML"]] + testthat::expect_true(grepl("select multiple", filter_html) && grepl('data-type="factor"', filter_html)) + + app$stop() + } +) + +test_that( + "Column selectors show labels if available" |> + vdoc[["add_spec"]](c(specs$listings$extra_column_selection_labels)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(duration = wait_for_idle_ms) + app$set_inputs("papo-listings-data_selector" = "cm") + app$wait_for_idle() + + select_extra_columns <- app$get_html(selector = "#papo-listings-column_selector") + + matches <- gregexpr('data-subtext="([^"]*)"', select_extra_columns) + data_subtexts <- regmatches(select_extra_columns, matches)[[1]] + data_subtexts <- gsub('data-subtext="|"', "", data_subtexts) + expect_contains(data_subtexts, c("Study Identifier", "Age", "Race")) + + app$stop() + } +) + +test_that( + "Message explains the lack of data for listings" |> + vdoc[["add_spec"]](c(specs$listings$no_data_message)), + { + skip("DT listings provide a 'No data' message by default") + } +) + +test_that( + "Column selectors show labels if available" |> + vdoc[["add_spec"]](c(specs$plots$common$tooltips)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(duration = wait_for_idle_ms) + + # ... [continued from R/mod_plots.R:#umeega] we recover the data from the export + slot + tooltips <- app$get_values()[["export"]][["papo-plot_contents-test_plot_data"]][["tooltips/Adverse Events Plot"]] + expect_true(length(tooltips) == 3 && all(nchar(tooltips) > 200)) + + app$stop() + } +) + +test_that( + "Mild adverse events are colored as such" |> + vdoc[["add_spec"]](c(specs$plots$common$palettes, specs$plots$range$grading)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(duration = wait_for_idle_ms) + + target_color <- grDevices::col2rgb(CONST$default_palette[["MILD"]]) + target_color_as_string <- paste0("rgba(", paste(target_color, collapse = ","), ",1)") + + ae_plot_first_color <- + app$get_values()[["export"]][["papo-plot_contents-test_plot_data"]][["plot_first_line_color/Adverse Events Plot"]] + expect_equal(target_color_as_string, ae_plot_first_color) + + app$stop() + } +) + +test_that( + "Message explains the lack of data for plots" |> + vdoc[["add_spec"]](c(specs$plots$common$no_data_message)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(wait_for_idle_ms) + app$click(input = "jump") + app$wait_for_idle(duration = wait_for_idle_ms) + expected <- "01-701-1033" + plot_messages <- app$get_values()[["export"]][["papo-plot_contents-test_plot_data"]][["plot_messages"]] + expect_contains(plot_messages, "* No Data for Adverse Events Plot.") + app$stop() + } +) + +test_that( + "Parameters for value plots can be selected from a drop-down menu" |> + vdoc[["add_spec"]](c(specs$plots$value$parameter_selection)), + { + test_pid <- "01-701-1028" + subjid_var <- "USUBJID" + lb_tests <- c("Alanine Aminotransferase", "Chloride", "Basophils") + vs_tests <- c("Pulse Rate", "Diastolic Blood Pressure", "Systolic Blood Pressure") + + shiny::testServer( + patient_plot_server, + arg = list( + id = "test", + subject_var = subjid_var, + subject_level_dataset = shiny::reactive(testd1_sl), + timeline_info = timeline_info, + extra_datasets = shiny::reactive(testd1_extra), + range_plots = range_plots, + value_plots = value_plots, + vline_vars = vline_vars, + palette = NULL + ), + { + session$setInputs(patient_selector = test_pid) + session$setInputs(Lab_plot = lb_tests) + session$setInputs(Vital_Sign_Plot = vs_tests) + session$flushReact() + expect_equal(input[["Lab_plot"]], lb_tests) + expect_equal(input[["Vital_Sign_Plot"]], vs_tests) + } + ) + } +) + +test_that( + "Events that exceed ranges get labelled with arrows" |> + vdoc[["add_spec"]](c(specs$plots$range$arrows)), + { + app <- shinytest2::AppDriver$new(root_app_url) + app$wait_for_idle(wait_for_idle_ms) + arrows <- app$get_values()[["export"]][["papo-plot_contents-test_plot_data"]][["arrow_right/Adverse Events Plot"]] + expect_equal(arrows, as.Date(c("2014-07-02", "2014-07-02", NA))) + app$stop() + } +) diff --git a/vignettes/.gitignore b/vignettes/.gitignore new file mode 100644 index 0000000..097b241 --- /dev/null +++ b/vignettes/.gitignore @@ -0,0 +1,2 @@ +*.html +*.R diff --git a/vignettes/a00-papo.Rmd b/vignettes/a00-papo.Rmd new file mode 100644 index 0000000..696990d --- /dev/null +++ b/vignettes/a00-papo.Rmd @@ -0,0 +1,287 @@ +--- +title: "Patient Profile Module" +output: rmarkdown::html_vignette +vignette: > + %\VignetteIndexEntry{Patient Profile Module} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + eval = FALSE, + collapse = TRUE, + comment = "#>" +) +``` + +This guide will help you configure the Patient Profile module for inclusion in DaVinci apps. + +## What does the Patient Profile module do? + +The DaVinci Patient Profile module displays patient information on a subject-level basis. +It is divided into three sections: summary, listings, and plots. + +- Summary: Snapshot of the patient's demographic information that doesn't change with visits. +- Listings: Information that changes with each visit. +- Plots: Visual depictions of events over time, such as adverse events or concomitant medication, + and point-like events like lab values or vital sign measurements. + +The following screenshot shows the module configured to display the popular sample `safetyData` dataset. +Notice the three sections under the titles "Patient Information", "Data Listings" and "Graphical Display": + + + +![](images/complete_display.jpg) + +The next section breaks down the necessary configuration steps to set up this display. + +The final section shows the resulting configuration. + +## How to configure the Patient Profile module? + +The `mod_patient_profile` function takes several arguments, some of which are optional: + +- `module_id`: This is a unique identifier for the Shiny module in your DaVinci app. + +- `subject_level_dataset_name`, `subjid_var`: These are the subject-level dataset name and unique subject identifier column respectively. + +- `sender_ids`: This optional parameter identifies modules that can request the display of target patient IDs. You can read more about it in the dedicated "Module Communication" article. + +- `summary`, `listings`, `plots`: These optional parameters allow you to customize what information is displayed in each of the three section. Let's take a look at each of them separately. + + +### Incremental configuration +As will become apparent, some of these parameters have fields, and some of those fields have subfields. **The complexity of this interface reflects its flexibility, but it can prove overwhelming**. To alleviate this situation, we've made sure that **this module is functional when partially configured and provides clear and helpful error messages when accidentally misconfigured**. + +When a DaVinci application containing a misconfigured `mod_patient_profile` starts it presents descriptive instructions on how to address the problem. Here's a screenshot showing three such help messages: + +If no error is displayed on application start, the blame for any unexpected problems the users encounter should fall on the authors of this module or the infrastructure providers. + +This forgiving behavior makes it possible to start with a minimal empty call to `dv.papo::mod_patient_profile()` and parameterize it incrementally until a satisfactory configuration is reached. + +### The `summary` parameter + +The `summary` parameter is a list that allows to customize the subject-level summary section. It is composed of: + +- `vars`: These are the values you want to display in the this section. They index into the dataset specified by `subject_level_dataset_name`. +- `column_count`: This is the number of columns for the summary section. + +Recall the summary section of the sample image at the beginning of this article: + + +The parameterization that generates that section is: +``` +summary = list( + vars = c("SUBJID", "SITEID", "ARM", + "TRTSDT", "TRTEDT", "AGE", + "RACE", "SEX", "BMIBL"), + column_count = 3 +) +``` +We've broken the `vars` field into three lines to highlight the one-to-one mapping between each var and the their counterpart on the image. + +The bold-faced descriptions of the variables are extracted from the `label` column attribute already present in the dataset. + +### The `listings` parameter + +The `listings` parameter is a named list of elements to include as listings in the "Data Listing" section. + +Recall the listings section in the sample image at the beginning of this article: + + +The parameterization that generates that section is: +``` +listings = list( + "Concomitant Medication" = list( + dataset = "cm" + ), + "Adverse Events" = list( + dataset = "adae", + default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV") + ) +) +``` +Notice how the names on the list (`"Concomitant Medication"` and `"Adverse Events"`) are used as the labels in the blue "Domain" selector. +The mandatory `dataset` field indicates which domain to display under which heading. The optional `default_vars` is the initial selection +of "Columns" to display on the listing. The user can modify that selection. + +The bold-faced listing headings are extracted from the `label` column attribute already present in the dataset. + + +### The `plots` parameter + +The plots parameter is a named list of elements to include as plots in the "Graphical Display" section. + +Recall the plots section in the sample image at the beginning of this article: + +The parameterization that generates that section is: +``` +plots = list( + timeline_info = c(trt_start_date = "TRTSDT", trt_end_date = "TRTEDT"), + range_plots = list( + "Concomitant Medication" = list( + dataset = "cm", + vars = c(start_date = "CMSTDT", end_date = "CMENDT", decode = "CMDECOD", + grading = "CMDECOD"), + tooltip = c() + ), + "Adverse Events" = list( + dataset = "adae", + vars = c(start_date = "ASTDT", end_date = "AENDT", decode = "AEDECOD", + grading = "AESEV", serious_ae = "AESER"), + tooltip = c("AE Start Day: " = "ASTDY", "AE End Day: " = "AENDY") + ) + ), + value_plots = list( + "Lab Values" = list( + dataset = "lb", + vars = c(analysis_param = "PARAM", analysis_val = "AVAL", analysis_date = "ADT", + analysis_indicator = "LBNRIND", range_low_limit = "A1LO", range_high_limit = "A1HI"), + tooltip = c() + ) + ), + vline_vars = c("Informed Consent Date" = "RFICDT") + ) +``` +As with the two previous sections, there is a clear mapping between the `plot` fields and their effect on the displayed charts. +Here's a brief summary of those fields: + +- `timeline_info` configures the extent of the horizontal time axis. +- `range_plots` and `value_plots` describe which plots to include. +- `vline_vars` and `vline_day_numbers` (optional and not used in the example) add extra vertical markers that run through all plots. +- `palette` (optional and not used in the example) is used to fine-tune the color of points, ranges and vertical markers on plots. + +And here's a more detailed account of their properties: + +#### The `plots/timeline_info` field +The `timeline_info` field is a list of date variables in the dataset specified by the `subject_level_dataset_name` parameter. The two mandatory +subfields are: + +- `trt_start_date`: Treatment Start Date, used also as Day 1 Reference Date to derive Study Day numbers. +- `trt_end_date`: Treatment End Date. + +There are two additional optional subfields: + +- `icf_date`: Informed Consent Form signing Date. +- `part_end_date`: Participation End Date. + +They usually envelop and extend the treatment start-end time range. Including them expands the horizontal time range of the plots. + +#### The `plots/range_plots` field +The `range_plots` field is a named list of elements to include as plots for range-like events (adverse events, concomitant medications, etc.). Each of them has three members: + +- `dataset`: Dataset name from which to pull the information. +- `vars`: Variables of interest for the event. They index into `dataset`: + + - `start_date` and `end_date`: Beginning and end of the range. + - `decode`: Description of the event. + - `grading`: Intensity of the event. Used for color-coding ranges. + - `serious_ae`: Marker of serious adverse event. Overlays a `SAE` legend on top of events that require special attention. + +- `tooltip`: Defines a block of text to display as hover information over the left edge of each range. It is specified as a named list of `dataset` variable names. The names of this list are included as literal text and honor three basic HTML formatting elements: ``, ``, `
`. The columns the values refer to are populated with the value on the dataset relevant to any given row. + +#### The `plots/value_plots` field +The `value_plots` field is a named list of elements to include as plots for value-like traces (lab measurements, vital signs, etc.). Each of them has three members: + +- `dataset`: Dataset name from which to pull the information. +- `vars`: Variables of interest for the event. Only the first three are mandatory. They index into `dataset`: + + - `analysis_param`: Variable describing the parameter to plot. + - `analysis_val`: Value associated to each time point. + - `analysis_date`: Date of sample collection. + - `analysis_indicator`: Used for color-coding the marker on the plot. Usually indicates whether a value is inside or outside of range. + - `range_low_limit`: Lower limit of the range considered normal for this particular parameter. + - `range_high_limit`: Higher limit of the range considered normal for this particular parameter. + - `summary_stats` : This variable supplements `analysis_val` and is useful for datasets that have more than one measurement per `analysis_date`. It should point to a variable that summarizes all measurements on a single visit through a centrality calculation (mean, median, etc.). + +- `tooltip`: Defines a block of text to display as hover information over the left edge of each range. It is specified as a named list of `dataset` variable names. The names of this list are included as literal text and honor three basic HTML formatting elements: ``, ``, `
`. The columns the values refer to are populated with the value on the dataset relevant to any given row. + +#### The `plots/vline_vars` field +The `vline_vars` field places vertical dashed lines on days indicated by this dataset columns. It indexes into the dataset `subject_level_dataset_name` and expects values of type `integer`, `Date` or `POSIXt`. + +#### The `plots/vline_day_numbers` field +The `vline_day_numbers` field requires a vector of integers, representing CDISC (non-zero) Study Days. It places vertical dashed lines on the positions corresponding to those days. + +#### The `plots/palette` field +The `palette` field requires a named list of colors. If a name on this list matches the text on a plot element, the associated color will be applied to that element. This mapping takes precedence over the built-in palette. It contains either an HTML (#xxxxxx) or an R color. As an example, if the desired color for an element tagged "Relevant" is yellow and for another tagged "Irrelevant" is gray, this would be the appropriate palette definition: +``` +palette = c("Relevant" = "yellow", "Irrelevant" = "gray") +``` + +## Complete sample configuration + +As promised, here's the configuration resulting from aggregating all the previous steps: + +``` +dv.papo::mod_patient_profile( + module_id = "papo", + subject_level_dataset_name = "adsl", + subjid_var = "USUBJID", + summary = list( + vars = c("SUBJID", "SITEID", "ARM", "TRTSDT", "TRTEDT", "AGE", "RACE", "SEX", "BMIBL"), + column_count = 3L + ), + listings = list( + "Concomitant Medication" = list( + dataset = "cm" + ), + "Adverse Events" = list( + dataset = "adae", + default_vars = c("ASTDT", "ASTDY", "AENDT", "AENDY", "AEDECOD", "AESEV") + ) + ), + plots = list( + timeline_info = c( + trt_start_date = "TRTSDT", + trt_end_date = "TRTEDT" + ), + range_plots = list( + "Concomitant Medication" = list( + dataset = "cm", + vars = c( + start_date = "CMSTDT", + end_date = "CMENDT", + decode = "CMDECOD", + grading = "CMDECOD" + ), + tooltip = c() + ), + "Adverse Events" = list( + dataset = "adae", + vars = c( + start_date = "ASTDT", + end_date = "AENDT", + decode = "AEDECOD", + grading = "AESEV", + serious_ae = "AESER" + ), + tooltip = c( + "AE Start Day: " = "ASTDY", + "AE End Day: " = "AENDY" + ) + ) + ), + value_plots = list( + "Lab Values" = list( + dataset = "lb", + vars = c( + analysis_param = "PARAM", + analysis_val = "AVAL", + analysis_date = "ADT", + analysis_indicator = "LBNRIND", + range_low_limit = "A1LO", + range_high_limit = "A1HI" + ), + tooltip = c() + ) + ), + vline_vars = c( + "Informed Consent Date" = "RFICDT" + ) + ) +) +``` diff --git a/vignettes/a01-data_requirements.Rmd b/vignettes/a01-data_requirements.Rmd new file mode 100644 index 0000000..083d1f0 --- /dev/null +++ b/vignettes/a01-data_requirements.Rmd @@ -0,0 +1,28 @@ +--- +title: "Data requirements" +output: rmarkdown::html_vignette +vignette: > + %\VignetteIndexEntry{Data requirements} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +Data sets and their variables to be used to display the patient profile must fulfill the conditions listed below: + +- The accepted types for date variables are (`Date`) or date-time (`POSIXt`) but not plain character strings. + +- All datasets must provide a unique shared subject identifier variable. + +- The mandatory subject-level dataset should also provide variables for: + - treatment start dates + - treatment end dates + +- All visit-dependent datasets used referred to by the `range_plots` parameter should additionally provide variables for : + - start dates + - end dates + - "decode" description of the event + +- All visit-dependent datasets used referred to by the `value_plots` parameter should additionally provide variables for : + - analysis date + - parameter + - value diff --git a/vignettes/a02-communication.Rmd b/vignettes/a02-communication.Rmd new file mode 100644 index 0000000..ed626ff --- /dev/null +++ b/vignettes/a02-communication.Rmd @@ -0,0 +1,45 @@ +--- +title: "Communication with other DaVinci modules" +output: rmarkdown::html_vignette +vignette: > + %\VignetteIndexEntry{Communication with other DaVinci modules} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + eval = FALSE, + collapse = TRUE, + comment = "#>" +) +``` + +DaVinci modules can direct `mod_patient_profile` to select and display information associated to any particular subject ID. When the Patient Profile is so instructed, it switches to the target subject ID and takes focus from the application, effectively *jumping* to a patient profile display as a result of a simple user interaction, such as a mouse click. + +Examples of modules implementing that functionality are `dv.clinlines` and several of the `dv.biomarker.general` displays. + +## Configuration + +Configuring `mod_patient_profile` to communicate with some other module usually involves setting up two parameters, one in each of the two modules participating in the exchange. On the receiver end, the `sender_ids` parameter lists the identifiers of modules Patient Profile will listen to. On the sender side, the specifics may vary, so we will provide an example using the `dv.clinlines` module. + +## Example + +This is a sketch of the portions of code relevant to establish communication between the Patient Profile and Clinical Timelines modules: + +```{r} +module_list <- list( + "Patient Profiles" = dv.papo::mod_patient_profile( + module_id = "mod1", + ..., # ommitted for brevity + sender_ids = c("mod2") + ), + "Clinical Timelines" = dv.clinlines::mod_clinical_timelines( + module_id = "mod2", + ..., # ommitted for brevity + receiver_id = "mod1" + ) +) +``` + +Notice how Patient Profile can specify more than one module as the source of "jumping" messages. diff --git a/vignettes/images/complete_display.jpg b/vignettes/images/complete_display.jpg new file mode 100644 index 0000000000000000000000000000000000000000..18678058a5dd6c285340d650df25b11a0c4a24ac GIT binary patch literal 153829 zcmeFa1zc52_dmQ34bq{2ba%I;(jB6JqI5|fLO_J0fP^$6NK2PNNr-?-N{2{Fmw*8% 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HcmV?d00001 diff --git a/vignettes/qc.Rmd b/vignettes/qc.Rmd new file mode 100644 index 0000000..87bb735 --- /dev/null +++ b/vignettes/qc.Rmd @@ -0,0 +1,32 @@ +--- +title: "Quality Control" +output: + rmarkdown::html_vignette +vignette: > + %\VignetteIndexEntry{Quality Control} + %\VignetteEngine{knitr::rmarkdown} + %\VignetteEncoding{UTF-8} +--- + +```{r, include = FALSE} +knitr::opts_chunk$set( + collapse = TRUE, + comment = "#>", + echo = FALSE +) +``` + +```{r, params, echo = FALSE, include = FALSE} +val_param_rds <- "../inst/validation/results/val_param.rds" +val_param_rds_exists <- file.exists(val_param_rds) +if (file.exists(val_param_rds)) params <- readRDS(val_param_rds) +``` + +```{r, results = "asis", echo = FALSE} +if (val_param_rds_exists) { + res <- knitr::knit_child("../inst/validation/val_report_child.Rmd", quiet = TRUE, envir = environment()) + cat(res, sep = "\n") +} else { + "No quality control results found" +} +```