Doc updates

Doc updates with status labels

R/alm.R

@@ -1,6 +1,10 @@
 #' @title Locate the next design point(s) for a (D)GP emulator or a bundle of (D)GP emulators using Active Learning MacKay (ALM)
 #'
-#' @description This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
 #'     or a bundle of (D)GP emulators using the Active Learning MacKay (ALM) criterion (see the reference below).
 #'
 #' @param object can be one of the following:
@@ -11,7 +15,7 @@
 #'     from which the next design point(s) are determined. If `object` is an instance of the `bundle` class and `aggregate` is not supplied, `x_cand` can also be a list.
 #'     The list must have a length equal to the number of emulators in `object`, with each element being a matrix representing the candidate set for a corresponding
 #'     emulator in the bundle. Defaults to `NULL`.
-#' @param n_start an integer that gives the number of initial design points to be used to determine next design point(s). This argument
+#' @param n_start `r new_badge("new")` an integer that gives the number of initial design points to be used to determine next design point(s). This argument
 #'     is only used when `x_cand` is `NULL`. Defaults to `20`.
 #' @param batch_size an integer that gives the number of design points to be chosen. Defaults to `1`.
 #' @param M `r new_badge("new")` the size of the conditioning set for the Vecchia approximation in the criterion calculation. This argument is only used if the emulator `object`
@@ -23,7 +27,7 @@
 #'     If a vector is provided, it will be converted to a two-column row matrix. The rows of the matrix correspond to input dimensions, and its
 #'     first and second columns correspond to the minimum and maximum values of the input dimensions. This
 #'     argument is only used when `x_cand = NULL`. Defaults to `NULL`.
-#' @param int a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
+#' @param int `r new_badge("new")` a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
 #'     all input dimensions. If a vector is provided, it should have a length equal to the input dimensions and will be applied to individual
 #'     input dimensions. This argument is only used when `x_cand = NULL`. Defaults to `FALSE`.
 #' @param aggregate an R function that aggregates scores of the ALM across different output dimensions (if `object` is an instance

R/design.R

@@ -1,6 +1,10 @@
 #' @title Sequential design of a (D)GP emulator or a bundle of (D)GP emulators
 #'
-#' @description This function implements sequential design and active learning for a (D)GP emulator or
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function implements sequential design and active learning for a (D)GP emulator or
 #'     a bundle of (D)GP emulators, supporting an array of popular methods as well as user-specified approaches.
 #'     It can also be used as a wrapper for Bayesian optimization methods.
 #'
@@ -13,7 +17,7 @@
 #'     from which the next design points are determined. Defaults to `NULL`.
 #' @param y_cand a matrix (with each row being a simulator evaluation and column being an output dimension) that gives the realizations
 #'    from the simulator at input positions in `x_cand`. Defaults to `NULL`.
-#' @param n_sample an integer that gives the size of a sub-set to be sampled from the candidate set `x_cand` at each step of the sequential design to determine the next
+#' @param n_sample `r new_badge("new")` an integer that gives the size of a sub-set to be sampled from the candidate set `x_cand` at each step of the sequential design to determine the next
 #'   design point, if `x_cand` is not `NULL`.
 #'
 #' Defaults to `200`.
@@ -59,7 +63,7 @@
 #' Defaults to `FALSE`.
 #' @param target a number or vector specifying the target evaluation metric value(s) at which the sequential design should terminate.
 #'     Defaults to `NULL`, in which case the sequential design stops after `N` steps. See the *Note* section below for further details about `target`.
-#' @param method an R function that determines the next design points to be evaluated by `f`. The function must adhere to the following rules:
+#' @param method `r new_badge("updated")` an R function that determines the next design points to be evaluated by `f`. The function must adhere to the following rules:
 #' - **First argument**: an emulator object, which can be one of the following:
 #'   - an instance of the `gp` class (produced by [gp()]);
 #'   - an instance of the `dgp` class (produced by [dgp()]);
@@ -76,7 +80,7 @@
 #'       represent the new design points for the corresponding emulator.
 #'
 #' See [alm()], [mice()], and [vigf()] for examples of built-in `method` functions. Defaults to [vigf()].
-#' @param batch_size an integer specifying the number of design points to select in a single iteration. Defaults to `1`.
+#' @param batch_size `r new_badge("new")` an integer specifying the number of design points to select in a single iteration. Defaults to `1`.
 #'     This argument is used by the built-in `method` functions [alm()], [mice()], and [vigf()].
 #'     If you provide a custom `method` function with an argument named `batch_size`, the value of `batch_size` will be passed to your function.
 #' @param eval an R function that computes a customized metric for evaluating emulator performance. The function must adhere to the following rules:

R/draw.R

@@ -1,6 +1,10 @@
 #' @title Validation and diagnostic plots for a sequential design
 #'
-#' @description This function draws diagnostic and validation plots for a sequential design of a (D)GP emulator or a bundle of (D)GP emulators.
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function draws diagnostic and validation plots for a sequential design of a (D)GP emulator or a bundle of (D)GP emulators.
 #'
 #' @param object can be one of the following emulator classes:
 #' * the S3 class `gp`.
@@ -13,7 +17,7 @@
 #' Defaults to `"rmse"`.
 #' @param log a bool indicating whether to plot RMSEs, log-losses (for DGP emulators with categorical likelihoods), or custom evaluation metrics on a log scale when `type = "rmse"`.
 #'     Defaults to `FALSE`.
-#' @param emulator an index or vector of indices of emulators packed in `object`. This argument is only used if `object` is an instance of the `bundle` class. When set to `NULL`, all
+#' @param emulator `r new_badge("updated")` an index or vector of indices of emulators packed in `object`. This argument is only used if `object` is an instance of the `bundle` class. When set to `NULL`, all
 #'     emulators in the bundle are drawn. Defaults to `NULL`.
 #' @param ... N/A.
 #'

R/lgp.R

@@ -1,6 +1,10 @@
 #' @title Linked (D)GP emulator construction
 #'
-#' @description This function constructs a linked (D)GP emulator for a model chain or network.
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function constructs a linked (D)GP emulator for a model chain or network.
 #'
 #' @param struc the structure of the linked emulator, which can take one of two forms:
 #' - `r lifecycle::badge("deprecated")` a list contains *L* (the number of layers in a systems of computer models) sub-lists,

R/mice.R

@@ -1,6 +1,10 @@
 #' @title Locate the next design point for a (D)GP emulator or a bundle of (D)GP emulators using MICE
 #'
-#' @description This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
 #'     or a bundle of (D)GP emulators using the Mutual Information for Computer Experiments (MICE), see the reference below.
 #'
 #' @param object can be one of the following:
@@ -20,11 +24,11 @@
 #' @param nugget_s the value of the smoothing nugget term used by MICE. Defaults to `1e-6`.
 #' @param workers  the number of processes to be used for the criterion calculation. If set to `NULL`,
 #'     the number of processes is set to `max physical cores available %/% 2`. Defaults to `1`.
-#' @param limits a two-column matrix that gives the ranges of each input dimension, or a vector of length two if there is only one input dimension.
+#' @param limits `r new_badge("new")` a two-column matrix that gives the ranges of each input dimension, or a vector of length two if there is only one input dimension.
 #'     If a vector is provided, it will be converted to a two-column row matrix. The rows of the matrix correspond to input dimensions, and its
 #'     first and second columns correspond to the minimum and maximum values of the input dimensions. This
 #'     argument is only used when `x_cand = NULL`. Defaults to `NULL`.
-#' @param int a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
+#' @param int `r new_badge("new")` a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
 #'     all input dimensions. If a vector is provided, it should have a length equal to the input dimensions and will be applied to individual
 #'     input dimensions. This argument is only used when `x_cand = NULL`. Defaults to `FALSE`.
 #' @param aggregate an R function that aggregates scores of the MICE across different output dimensions (if `object` is an instance

R/plot.R

@@ -1,14 +1,18 @@
 #' @title Validation plots of a constructed GP, DGP, or linked (D)GP emulator
 #'
-#' @description This function draws validation plots of a GP, DGP, or linked (D)GP emulator.
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function draws validation plots of a GP, DGP, or linked (D)GP emulator.
 #'
 #' @param x can be one of the following emulator classes:
 #' * the S3 class `gp`.
 #' * the S3 class `dgp`.
 #' * the S3 class `lgp`.
 #' @param x_test same as that of [validate()].
 #' @param y_test same as that of [validate()].
-#' @param dim if `dim = NULL`, the index of an emulator's input within the design will be shown on the x-axis in validation plots. Otherwise, `dim` indicates
+#' @param dim `r new_badge("updated")` if `dim = NULL`, the index of an emulator's input within the design will be shown on the x-axis in validation plots. Otherwise, `dim` indicates
 #'     which dimension of an emulator's input will be shown on the x-axis in validation plots:
 #' * If `x` is an instance of the `gp` of `dgp` class, `dim` is an integer.
 #' * `r lifecycle::badge("deprecated")` If `x` is an instance of the `lgp` class created by [lgp()] without specifying the `struc` argument in data frame form, `dim` can be:

R/prediction.R

@@ -1,7 +1,10 @@
 #' @title Prediction from GP, DGP, or linked (D)GP emulators
 #'
-#' @description This function implements single-core or multi-core prediction (with or without multi-threading)
-#'     from GP, DGP, or linked (D)GP emulators.
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function implements prediction from GP, DGP, or linked (D)GP emulators.
 #'
 #' @param object an instance of the `gp`, `dgp`, or `lgp` class.
 #' @param x the testing input data:

R/serialization.R

@@ -1,6 +1,10 @@
 #' @title Serialize the constructed emulator
 #'
-#' @description This function serialize the constructed emulator.
+#' @description
+#'
+#' `r new_badge("new")`
+#'
+#' This function serialize the constructed emulator.
 #'
 #' @param object an instance of the S3 class `gp`, `dgp`, `lgp`, or `bundle`.
 #' @param light a bool indicating if a light version of the constructed emulator (that requires a small storage) will be serialized.
@@ -98,7 +102,11 @@ serialize <- function(object, light = TRUE) {
 
 #' @title Restore the serialized emulator
 #'
-#' @description This function restores the serialized emulator created by [serialize()].
+#' @description
+#'
+#' `r new_badge("new")`
+#'
+#' This function restores the serialized emulator created by [serialize()].
 #'
 #' @param object the serialized object of an emulator.
 #'

R/vigf.R

@@ -1,6 +1,10 @@
 #' @title Locate the next design point for a (D)GP emulator or a bundle of (D)GP emulators using VIGF
 #'
-#' @description This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
+#' @description
+#'
+#' `r new_badge("updated")`
+#'
+#' This function searches from a candidate set to locate the next design point(s) to be added to a (D)GP emulator
 #'     or a bundle of (D)GP emulators using the Variance of Improvement for Global Fit (VIGF). For VIGF on GP emulators, see the reference below.
 #'
 #' @param object can be one of the following:
@@ -11,7 +15,7 @@
 #'     from which the next design point(s) are determined. If `object` is an instance of the `bundle` class and `aggregate` is not supplied, `x_cand` can also be a list.
 #'     The list must have a length equal to the number of emulators in `object`, with each element being a matrix representing the candidate set for a corresponding
 #'     emulator in the bundle. Defaults to `NULL`.
-#' @param n_start an integer that gives the number of initial design points to be used to determine next design point(s). This argument
+#' @param n_start `r new_badge("new")` an integer that gives the number of initial design points to be used to determine next design point(s). This argument
 #'     is only used when `x_cand` is `NULL`. Defaults to `10`.
 #' @param batch_size an integer that gives the number of design points to be chosen.
 #'     Defaults to `1`.
@@ -20,11 +24,11 @@
 #' @param workers the number of processes to be used for design point selection. If set to `NULL`,
 #'     the number of processes is set to `max physical cores available %/% 2`. Defaults to `1`. The argument does not currently support Windows machines when the `aggregate`
 #'     function is provided, due to the significant overhead caused by initializing the Python environment for each worker under spawning.
-#' @param limits a two-column matrix that gives the ranges of each input dimension, or a vector of length two if there is only one input dimension.
+#' @param limits `r new_badge("new")` a two-column matrix that gives the ranges of each input dimension, or a vector of length two if there is only one input dimension.
 #'     If a vector is provided, it will be converted to a two-column row matrix. The rows of the matrix correspond to input dimensions, and its
 #'     first and second columns correspond to the minimum and maximum values of the input dimensions. This
 #'     argument is only used when `x_cand = NULL`. Defaults to `NULL`.
-#' @param int a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
+#' @param int `r new_badge("new")` a bool or a vector of bools that indicates if an input dimension is an integer type. If a single bool is given, it will be applied to
 #'     all input dimensions. If a vector is provided, it should have a length equal to the input dimensions and will be applied to individual
 #'     input dimensions. This argument is only used when `x_cand = NULL`. Defaults to `FALSE`.
 #' @param aggregate an R function that aggregates scores of the VIGF across different output dimensions (if `object` is an instance