Line length linting, CI integration.

Author: kylesnap

.github/workflows/R-CMD-check.yaml

@@ -0,0 +1,51 @@
+# Workflow derived from https://github.com/r-lib/actions/tree/v2/examples
+# Need help debugging build failures? Start at https://github.com/r-lib/actions#where-to-find-help
+on:
+  push:
+    branches: [main, master]
+  pull_request:
+
+name: R-CMD-check.yaml
+
+permissions: read-all
+
+jobs:
+  R-CMD-check:
+    runs-on: ${{ matrix.config.os }}
+
+    name: ${{ matrix.config.os }} (${{ matrix.config.r }})
+
+    strategy:
+      fail-fast: false
+      matrix:
+        config:
+          - {os: macos-latest,   r: 'release'}
+          - {os: windows-latest, r: 'release'}
+          - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
+          - {os: ubuntu-latest,   r: 'release'}
+          - {os: ubuntu-latest,   r: 'oldrel-1'}
+
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+      R_KEEP_PKG_SOURCE: yes
+
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-pandoc@v2
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          r-version: ${{ matrix.config.r }}
+          http-user-agent: ${{ matrix.config.http-user-agent }}
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::rcmdcheck
+          needs: check
+
+      - uses: r-lib/actions/check-r-package@v2
+        with:
+          upload-snapshots: true
+          build_args: 'c("--no-manual","--compact-vignettes=gs+qpdf")'

.github/workflows/pkgcheck.yaml

@@ -0,0 +1,23 @@
+name: pkgcheck
+
+# This will cancel running jobs once a new run is triggered
+concurrency:
+  group: ${{ github.workflow }}-${{ github.head_ref }}
+  cancel-in-progress: true
+
+on:
+  # Manually trigger the Action under Actions/pkgcheck
+  workflow_dispatch:
+  # Run on every push to main
+  push:
+    branches:
+      - main
+      - ropensci_submission
+
+jobs:
+  pkgcheck:
+    runs-on: ubuntu-latest
+    permissions:
+      issues: write
+    steps:
+      - uses: ropensci-review-tools/pkgcheck-action@main

.github/workflows/test-coverage.yaml

@@ -34,15 +34,16 @@ jobs:
             clean = FALSE,
             install_path = file.path(normalizePath(Sys.getenv("RUNNER_TEMP"), winslash = "/"), "package")
           )
+          print(cov)
           covr::to_cobertura(cov)
         shell: Rscript {0}
 
-      - uses: codecov/codecov-action@v4
+      - uses: codecov/codecov-action@v5
         with:
           # Fail if error if not on PR, or if on PR and token is given
           fail_ci_if_error: ${{ github.event_name != 'pull_request' || secrets.CODECOV_TOKEN }}
-          file: ./cobertura.xml
-          plugin: noop
+          files: ./cobertura.xml
+          plugins: noop
           disable_search: true
           token: ${{ secrets.CODECOV_TOKEN }}
 

R/as_draws.R

@@ -40,7 +40,11 @@
 #'  summarize_draws()
 #'
 #' # View the radial coordinate in the unit-space over the run
-#' dm_rad <- as_draws_rvars(ernest_run_example, units = "unit_cube", radial = TRUE)
+#' dm_rad <- as_draws_rvars(
+#'  ernest_run_example,
+#'  units = "unit_cube",
+#'  radial = TRUE
+#' )
 #' plot(
 #'   x = ernest_run_example$log_volume,
 #'   y = draws_of(dm_rad$.radial),

R/calculate.R

@@ -1,5 +1,9 @@
 #' Estimate Evidence using a Nested Sampling Run
 #'
+#' Computes evidence and related quantities from a nested
+#' sampling run, optionally by simulating the volumes of each nested
+#' likelihood shell.
+#'
 #' @param x (ernest_run) An `ernest_run` object.
 #' @inheritParams rlang::args_dots_empty
 #' @param ndraws (positive integer or zero, optional) The number of log volume
@@ -22,21 +26,21 @@
 #' Each column is returned as an [posterior::rvar()] vector.
 #'
 #' @details
-#' Use `calculate()` to simulate the estimation error nested sampling runs caused
-#' by approximating the change in log volume between iterations. Given the
-#' use of ordered log likelihood restricted prior sampling, these volumes can be
-#' modelled as the order statistics of a uniform random variable. Ernest uses the
-#' following distributions to perform this simulation:
+#' Use `calculate()` to simulate the estimation error nested sampling runs
+#' caused by approximating the change in log volume between iterations. Given
+#' the use of ordered log likelihood restricted prior sampling, these volumes
+#' can be modelled as the order statistics of a uniform random variable.
+#' Ernest uses the following distributions to perform this simulation:
 #'
 #' * Constant number of live points: At each iteration, the point with the
 #' lowest likelihood is replaced by a new sample constrained to a higher
 #' likelihood region. Under this setup, the shrinkage in prior volume at
 #' iteration `i` can be shown to follow the Beta distribution.
 #' * Decreasing number of live points: At the end of the sampling run, the
-#' remaining live points are added to the dead point set. This introduces a discrete
-#' stepwise behavior in volume shrinkage. Ernest uses a transformation of variables
-#' drawn from the exponential distribution to simulate the corresponding changes
-#' in volume.
+#' remaining live points are added to the dead point set. This introduces a
+#' discrete stepwise behavior in volume shrinkage. Ernest uses a transformation
+#' of variables drawn from the exponential distribution to simulate the
+#' corresponding changes in volume.
 #'
 #' @references See Appendix A6 of Speagle, J. (2020).
 #
@@ -158,9 +162,11 @@ summary.ernest_estimate <- function(object, ...) {
 format.ernest_estimate <- function(x, ...) {
   cli::cli_format_method({
     cli::cli_div(theme = list(.val = list(digits = 3)))
-    cli::cli_bullets(
-      "An {.cls ernest_calculate}: {attr(x, 'ndraws')} draws x {length(x$log_lik)} iterations"
-    )
+    ndraws <- attr(x, "ndraws")
+    iter <- length(x$log_lik)
+    cli::cli_bullets(c(
+      "An {.cls ernest_calculate}: {ndraws} draws x {iter} iterations"
+    ))
   })
 }
 

R/likelihood-class.R

@@ -1,7 +1,8 @@
 #' Prepare a likelihood function for nested sampling
 #'
 #' Creates a modified version of a log. likelihood function that always returns
-#' either a finite value or `-Inf` for each vector of parameters that is provided.
+#' either a finite value or `-Inf` for each vector of parameters that is
+#' provided.
 #'
 #' @param fn (uni-variate function) The log-likelihood function (see Details).
 #' @param error_action (case-sensitive string) Action to perform once `fn`
@@ -28,9 +29,9 @@
 #' cause errors.
 #'
 #' @details
-#' Model likelihoods should be provided as a log density function. It is expected
-#' that `fn` should take in exactly one argument; likelihood functions that
-#' take in multiple non-default arguments should be entered as anonymous
+#' Model likelihoods should be provided as a log density function. It is
+#' expected that `fn` should take in exactly one argument; likelihood functions
+#' that take in multiple non-default arguments should be entered as anonymous
 #' functions (see [rlang::as_function()]).
 #'
 #' It is expected that `fn` returns a scalar finite values or `-Inf` for each
@@ -50,7 +51,8 @@
 #' @srrstats {G2.14, G2.14a, G2.14b, G2.14c, G2.15} create_likelihood catches
 #' missing values produced during a run and acts upon them based on user-desired
 #' behaviour.
-#' @srrstats {G2.16} Value handling is also performed for other undefined values.
+#' @srrstats {G2.16} Value handling is also performed for other undefined
+#' values.
 #'
 #' @examples
 #' # A 3D Gaussian likelihood function
@@ -264,7 +266,7 @@ format.ernest_likelihood <- function(x, ...) {
       ">" = "{.arg nonfinite_action} = {.val {attr(x, 'nonfinite_action')}}"
     ))
     cli::cat_line()
-    cli::cli_code(format(attr(x, 'body')))
+    cli::cli_code(format(attr(x, "body")))
   })
 }
 

R/lrps-class.R

@@ -38,7 +38,7 @@ ernest_lrps <- R6Class(
 
     update = function(...) {
       private$n_call <- 0L
-      return(self)
+      self
     },
 
     find_point = function(unit) {
@@ -109,7 +109,8 @@ ernest_lrps <- R6Class(
 
 #' Uniform LRPS Sampler (Internal)
 #'
-#' Internal R6 subclass for uniform sampling in the unit cube under a likelihood constraint.
+#' Internal R6 subclass for uniform sampling in the unit cube under a likelihood
+#' constraint.
 #'
 #' @keywords internal
 #' @noRd
@@ -152,7 +153,8 @@ uniform_lrps <- R6Class(
 
 #' Random Walk LRPS Sampler (Internal)
 #'
-#' Internal R6 subclass for random walk sampling in the unit cube with adaptive step size.
+#' Internal R6 subclass for random walk sampling in the unit cube with adaptive
+#' step size.
 #'
 #' @param steps Number of random walk steps.
 #' @param epsilon Initial step size.

R/nested_sampling.R

@@ -27,6 +27,21 @@
 #'
 #' @return An [ernest_sampler] object, prepared for nested sampling.
 #'
+#' @details
+#' This function prepares an `ernest_sampler` object for performing nested
+#' sampling, given a log-likelihood function, prior, and sampler specification.
+#' It checks that the provided log-likelihood and prior are compatible by
+#' performing a basic sanity check by evaluating the log-likelihood at the
+#' center of the prior space. This check ensures that the log-likelihood
+#' returns a finite value or `-Inf` for typical parameter values.
+#'
+#' The sanity check may fail even if `log_lik` is well-specified, for example
+#' if the prior's support does not include the test point
+#' (the center of the prior hypercube), or if the log-likelihood is only
+#' defined for a subset of the parameter space. In such cases, silencing the
+#' warning from `nested_sampling`` may require you to adjust the prior or
+#' adjust the `on_warning` argument.
+#'
 #' @export
 #' @examples
 #' prior <- create_uniform_prior(n_dim = 2, lower = -1, upper = 1)

R/plot.R

@@ -14,7 +14,9 @@
 #'
 #' The plot is faceted in three frames. The horizontal axis shows values of log.
 #' volume: If `x` is an `ernest_run` these estimates are derived from the run,
-#' if `x` is an `ernest_estimate` (or `ndraws != 0`), these values are simulated.
+#' if `x` is an `ernest_estimate` (or `ndraws != 0`), these values are
+#' simulated.
+#' 
 #' The three `y` axes are as follows:
 #'
 #' * **Evidence:** Estimate with a corresponding error ribbon drawn from either
@@ -28,11 +30,12 @@
 #' an error ribbon is drawn with the HDCI of this estimate.
 #'
 #' @note For `ernest_estimate`, `ndraws` must be sufficiently large to calculate
-#' HDI. If HDI calculation fails, the user will be warned and an `ernest_run` plot
-#' will be generated instead.
+#' HDI. If HDI calculation fails, the user will be warned and an `ernest_run`
+#' plot will be generated instead.
 #'
-#' @seealso [calculate()] for generating `ernest_estimate` objects; also, [visualize()] to
-#' plot the posterior distributions of the parameters from a run.
+#' @seealso [calculate()] for generating `ernest_estimate` objects; also,
+#' [visualize()] to plot the posterior distributions of the parameters from a
+#' run.
 #'
 #' @rdname plot.ernest
 #' @export

R/run-class.R

@@ -132,11 +132,18 @@ new_ernest_run <- function(res, n_live, n_dead, live_order, seed) {
 #' @export
 format.ernest_run <- function(x, ...) {
   smry <- summary(x)
+  log_z <- smry$log_evidence
+  log_z_sd <- smry$log_evidence_err
   cli::cli_format_method({
     cli::cli_div(theme = list(.val = list(digits = 3)))
+    first_line <- sprintf(
+      "%s %s",
+      "An {.cls ernest_run}:",
+      "{x$n_points} points x {x$n_iter} iter x {x$n_calls} lik. calls"
+    )
     cli::cli_bullets(c(
-      "An {.cls ernest_run}: {x$n_points} points x {x$n_iter} iter x {x$n_calls} lik. calls",
-      ">" = "Log. Evidence: {.val {smry$log_evidence}} \U00B1 {.val {smry$log_evidence_err}}"
+      first_line,
+      ">" = "Log. Evidence: {.val {log_z}} \U00B1 {.val {log_z_sd}}"
     ))
   })
 }
@@ -157,8 +164,8 @@ print.ernest_run <- function(x, ...) {
 #' @return An object of class `summary.ernest_run`, a list with:
 #' * `n_iter`: Number of iterations (number of dead points).
 #' * `n_points`: Number of live points at the end of the run.
-#' * `log_volume`, `log_evidence`, `log_evidence_err`: The final estimates of the
-#' quantities performed by the run that generated `object`.
+#' * `log_volume`, `log_evidence`, `log_evidence_err`: The final estimates of
+#' the quantities performed by the run that generated `object`.
 #' * `run`, A tibble with `n_iter + n_points` rows, containing the vectors
 #'  `call`, `log_lik`, `log_volume`, `log_weight`, `log_evidence`,
 #'  `log_evidence_err`, and `information`.