Updated examples (#72)

* Moved some auxiliary functions to internal

* Update GeoTox example

* Updated GeoTox S3 examples

* Increment version number to 0.1.4

DESCRIPTION

@@ -1,6 +1,6 @@
 Package: GeoTox
 Title: Spatiotemporal Mixture Risk Assessment
-Version: 0.1.3
+Version: 0.1.4
 Authors@R: c(
     person("Skylar", "Marvel", , "[email protected]", role = c("aut", "ctb"), comment = c(ORCID = "0000-0002-2971-9743")),
     person("David", "Reif", , "[email protected]", role = c("aut", "ctb"), comment = c(ORCID = "0000-0001-7815-6767")),

NAMESPACE

@@ -15,8 +15,6 @@ export(get_fixed_css)
 export(get_fixed_obesity)
 export(get_fixed_other)
 export(get_fixed_params)
-export(hill_conc)
-export(hill_val)
 export(plot_exposure)
 export(plot_hill)
 export(plot_resp)

NEWS.md

@@ -1,4 +1,5 @@
-# GeoTox 0.1.3
+# GeoTox 0.1.4
+- Updated unit test coverage and function examples
 
 # GeoTox 0.0.1
 - Adding supporting documents to the `GeoTox` repository such as this news.md, issue templates, and contributor's guide

R/GeoTox.R

@@ -38,7 +38,7 @@
 #' # Plot hill fits
 #' plot(geoTox, type = "hill")
 #' # Plot exposure data
-#' plot(geoTox, type = "exposure")
+#' plot(geoTox, type = "exposure", ncol = 5)
 #' # Plot response data
 #' plot(geoTox)
 #' plot(geoTox, assays = "TOX21_H2AX_HTRF_CHO_Agonist_ratio")

R/calc_concentration_response.R

@@ -11,9 +11,23 @@
 #' generalized concentration addition response, the independent action
 #' response, and a hazard quotient
 #'
-#' @return data frame
-#'
+#' @return list of data frames
 #' @export
+#' 
+#' @examples
+#' C_invitro <- list(
+#'   matrix(1:8 / 1e3, ncol = 2, dimnames = list(NULL, c("c1", "c2"))),
+#'   matrix(9:16 / 1e3, ncol = 2, dimnames = list(NULL, c("c1", "c2")))
+#' )
+#' hill_params <- fit_hill(
+#'   data.frame(chem = rep(c("c1", "c2"), each = 3),
+#'              logc = c(-1, 0, 1, 0, 1, 2),
+#'              resp = c(10, 5, 0, 4, 2, 0) / 10),
+#'   chem = "chem"
+#' )
+#'
+#' calc_concentration_response(C_invitro, hill_params)
+#' calc_concentration_response(C_invitro, hill_params, fixed = TRUE)
 calc_concentration_response <- function(C_invitro,
                                         hill_params,
                                         max_mult = 1.5,

R/calc_independent_action.R

@@ -25,6 +25,15 @@
 #' response function for each chemical.
 #' 
 #' @seealso \code{\link{hill_val}}
+#' 
+#' @examples
+#' n_chem <- 5
+#' conc <- 10^sample(-1:4, n_chem, replace = TRUE)
+#' max <- 80 * runif(n_chem)
+#' AC50 <- 10^(5 * runif(n_chem) - 1)
+#' Emax <- 100
+#' 
+#' calc_independent_action(conc, max, AC50, Emax)
 calc_independent_action <- function(conc, max, AC50, Emax, n = 1) {
 
   # if (any(max > Emax)) {

R/calculate_response.R

@@ -16,23 +16,27 @@
 #' [calc_concentration_response]
 #' 
 #' @examples
-#' # Create GeoTox object
-#' geoTox <- GeoTox()
+#' # Use a subset of the package data for demonstration purposes
+#' set.seed(2357)
+#' n <- 10 # Population size
+#' m <- 5 # Number of regions
+#' idx <- if (m < 100) sample(1:100, m) else 1:100
 #'
-#' # The following fields are required inputs
-#' geoTox$IR <- 2
-#' geoTox$C_ext <- matrix(3)
-#' geoTox$C_ss <- 5
-#' geoTox$hill_params <- fit_hill(data.frame(logc = c(-1, 0, 1),
-#'                                           resp = c(10, 5, 0)))
+#' # Create GeoTox object and populate required fields
+#' geoTox <- GeoTox() |>
+#'   # Simulate populations for each region
+#'   simulate_population(age = split(geo_tox_data$age, ~FIPS)[idx],
+#'                       obesity = geo_tox_data$obesity[idx, ],
+#'                       exposure = split(geo_tox_data$exposure, ~FIPS)[idx],
+#'                       simulated_css = geo_tox_data$simulated_css,
+#'                       n = n) |>
+#'   # Estimated Hill parameters
+#'   set_hill_params(geo_tox_data$dose_response |>
+#'                     fit_hill(assay = "endp", chem = "casn") |>
+#'                     dplyr::filter(!tp.sd.imputed, !logAC50.sd.imputed))
 #'
-#' # Calculate response
-#' geoTox <- calculate_response(geoTox)
-#' 
-#' # The following fields will be computed
-#' geoTox$D_int
-#' geoTox$C_invitro
-#' geoTox$resp
+#' # Response computations can now be done
+#' geoTox <- geoTox |> calculate_response()
 calculate_response <- function(x, ...) {
 
   # Update parameters

R/compute_sensitivity.R

@@ -6,6 +6,30 @@
 #'
 #' @return output from [calc_concentration_response]
 #' @export
+#' 
+#' @examples
+#' # Use a subset of the package data for demonstration purposes
+#' set.seed(2357)
+#' n <- 10 # Population size
+#' m <- 5 # Number of regions
+#' idx <- if (m < 100) sample(1:100, m) else 1:100
+#'
+#' # Create GeoTox object and populate required fields
+#' geoTox <- GeoTox() |>
+#'   # Simulate populations for each region
+#'   simulate_population(age = split(geo_tox_data$age, ~FIPS)[idx],
+#'                       obesity = geo_tox_data$obesity[idx, ],
+#'                       exposure = split(geo_tox_data$exposure, ~FIPS)[idx],
+#'                       simulated_css = geo_tox_data$simulated_css,
+#'                       n = n) |>
+#'   # Estimated Hill parameters
+#'   set_hill_params(geo_tox_data$dose_response |>
+#'                     fit_hill(assay = "endp", chem = "casn") |>
+#'                     dplyr::filter(!tp.sd.imputed, !logAC50.sd.imputed))
+#'
+#' # Sensitivity computations can now be done
+#' age_resp <- geoTox |> compute_sensitivity()
+#' obesity_resp <- geoTox |> compute_sensitivity(vary = "obesity")
 compute_sensitivity <- function(x,
                                 vary = c("age", "obesity", "css_params",
                                          "fit_params", "C_ext"),

R/hill_conc.R

@@ -8,8 +8,9 @@
 #' @param AC50 concentration of half-maximal response
 #' @param n Hill coefficient (slope)
 #'
+#' @keywords internal
+#'
 #' @return concentration in regular space
-#' @export
 #' 
 #' @details
 #' This is a regular space version of

R/hill_val.R

@@ -8,8 +8,9 @@
 #' @param AC50 concentration of half-maximal response
 #' @param n Hill coefficient (slope)
 #'
+#' @keywords internal
+#'
 #' @return response value
-#' @export
 #' 
 #' @details
 #' This is a regular space version of

R/obj_ECx.R

@@ -11,6 +11,8 @@
 #' @param max maximal (asymtotic) response
 #' @param AC50 concentrations of half-maximal response
 #'
+#' @keywords internal
+#'
 #' @return objective value
 obj_ECx <- function(conc_mix, resp, conc, max, AC50) {
   x <- hill_conc(resp, max, AC50, 1)

R/obj_GCA.R

@@ -9,6 +9,8 @@
 #' @param max maximal (asymtotic) responses
 #' @param AC50 concentrations of half-maximal response
 #'
+#' @keywords internal
+#'
 #' @return objective value
 obj_GCA <- function(ln_resp, conc, max, AC50) {
   # Solving for the efficacy on the natural log-scale. This allows for

R/obj_hill.R

@@ -4,6 +4,8 @@
 #' @param log10_conc base-10 log scale concentration
 #' @param resp response
 #'
+#' @keywords internal
+#'
 #' @return value of the objective function
 obj_hill <- function(par, log10_conc, resp) {
 

R/plot_sensitivity.R

@@ -20,15 +20,15 @@
 #'                        c("sample", metric)))
 #' }
 #' 
-#' x <- GeoTox()
-#' x$resp <- make_data()
-#' x$sensitivity <- list(age = make_data(),
-#'                       obesity = make_data(),
-#'                       css_params = make_data(),
-#'                       fit_params = make_data(),
-#'                       C_ext = make_data())
+#' geoTox <- GeoTox()
+#' geoTox$resp <- make_data()
+#' geoTox$sensitivity <- list(age = make_data(),
+#'                            obesity = make_data(),
+#'                            css_params = make_data(),
+#'                            fit_params = make_data(),
+#'                            C_ext = make_data())
 #' 
-#' plot_sensitivity(x)
+#' plot_sensitivity(geoTox)
 plot_sensitivity <- function(x,
                              metric = "GCA.Eff",
                              assay = NULL,

R/sensitivity_analysis.R

@@ -19,6 +19,29 @@
 #'
 #' @return The same GeoTox object with added `sensitivity` field.
 #' @export
+#' 
+#' @examples
+#' # Use a subset of the package data for demonstration purposes
+#' set.seed(2357)
+#' n <- 10 # Population size
+#' m <- 5 # Number of regions
+#' idx <- if (m < 100) sample(1:100, m) else 1:100
+#'
+#' # Create GeoTox object and populate required fields
+#' geoTox <- GeoTox() |>
+#'   # Simulate populations for each region
+#'   simulate_population(age = split(geo_tox_data$age, ~FIPS)[idx],
+#'                       obesity = geo_tox_data$obesity[idx, ],
+#'                       exposure = split(geo_tox_data$exposure, ~FIPS)[idx],
+#'                       simulated_css = geo_tox_data$simulated_css,
+#'                       n = n) |>
+#'   # Estimated Hill parameters
+#'   set_hill_params(geo_tox_data$dose_response |>
+#'                     fit_hill(assay = "endp", chem = "casn") |>
+#'                     dplyr::filter(!tp.sd.imputed, !logAC50.sd.imputed))
+#'
+#' # Sensitivity analysis can now be done
+#' geoTox <- geoTox |> sensitivity_analysis()
 sensitivity_analysis <- function(x,
                                  max_mult = list(NULL, NULL, NULL,
                                                  1.2, NULL)) {

R/simulate_population.R

@@ -22,15 +22,20 @@
 #' @export
 #'
 #' @examples
-#' # For information about geo_tox_data, see:
-#' # vignette("package_data", package = "GeoTox")
-#' 
-#' geoTox <- GeoTox() |> 
-#'   simulate_population(age = split(geo_tox_data$age, ~FIPS)[1:5],
-#'                       obesity = geo_tox_data$obesity[1:5, ],
-#'                       exposure = split(geo_tox_data$exposure, ~FIPS)[1:5],
+#' # Use a subset of the package data for demonstration purposes
+#' set.seed(2357)
+#' n <- 10 # Population size
+#' m <- 5 # Number of regions
+#' idx <- if (m < 100) sample(1:100, m) else 1:100
+#'
+#' # Create GeoTox object
+#' geoTox <- GeoTox() |>
+#'   # Simulate populations for each region
+#'   simulate_population(age = split(geo_tox_data$age, ~FIPS)[idx],
+#'                       obesity = geo_tox_data$obesity[idx, ],
+#'                       exposure = split(geo_tox_data$exposure, ~FIPS)[idx],
 #'                       simulated_css = geo_tox_data$simulated_css,
-#'                       n = 10)
+#'                       n = n)
 simulate_population <- function(x, age = NULL, obesity = NULL, exposure = NULL,
                                 simulated_css = NULL, ...) {
 

_pkgdown.yml

@@ -43,10 +43,8 @@ reference:
 - subtitle: Auxiliary
   desc: Auxillary and helper functions
 - contents:
-  - starts_with("fit_")
+  - fit_hill
   - starts_with("get_")
-  - starts_with("hill_")
-  - starts_with("obj_")
 - subtitle: Datasets
   desc: Package datasets
 - contents: