Merge pull request #33 from reichlab/prepare-for-cran

Prepare for cran (mainly linting)

.Rbuildignore

@@ -7,3 +7,4 @@
 ^docs$
 ^pkgdown$
 ^\.github$
+^\.lintr$

.github/workflows/lint.yaml

@@ -0,0 +1,34 @@
+# 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:
+    branches: [main, master]
+
+name: lint
+
+permissions: read-all
+
+jobs:
+  lint:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+    steps:
+      - uses: actions/checkout@v4
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::lintr, local::.
+          needs: lint
+
+      - name: Lint
+        run: lintr::lint_package()
+        shell: Rscript {0}
+        env:
+          LINTR_ERROR_ON_LINT: true

.gitignore

@@ -5,3 +5,4 @@ inst/doc
 docs
 
 *.Rproj
+/dev

.lintr

@@ -0,0 +1,5 @@
+linters: linters_with_defaults(
+    line_length_linter = line_length_linter(120L),
+    commented_code_linter = NULL,
+    object_name_linter = NULL
+  )

DESCRIPTION

@@ -1,33 +1,37 @@
 Package: distfromq
 Title: Reconstruct a Distribution from a Collection of Quantiles
 Version: 1.0.4
-Authors@R: 
-    c(person("Evan", "Ray", , "[email protected]", role = c("aut", "cre")),
-    person("Aaron", "Gerding", , "[email protected]", role = c("aut")),
-    person("Li", "Shandross", , "[email protected]", role = c("ctb")),
-    person("Nick", "Reich", , "[email protected]", role = c("ctb")))
-Description: Given a set of predictive quantiles from a distribution, estimate
-    the distribution and create `d`, `p`, `q`, and `r` functions to evaluate its
-    density function, distribution function, and quantile function, and generate
-    random samples. On the interior of the provided quantiles, an interpolation
-    method such as a monotonic cubic spline is used; the tails are approximated
-    by a location-scale family.
+Authors@R: c(
+    person("Evan", "Ray", , "[email protected]", role = c("aut", "cre")),
+    person("Aaron", "Gerding", , "[email protected]", role = "aut"),
+    person("Li", "Shandross", , "[email protected]", role = "ctb"),
+    person("Nick", "Reich", , "[email protected]", role = "ctb")
+  )
+Description: Given a set of predictive quantiles from a distribution,
+    estimate the distribution and create `d`, `p`, `q`, and `r` functions
+    to evaluate its density function, distribution function, and quantile
+    function, and generate random samples. On the interior of the provided
+    quantiles, an interpolation method such as a monotonic cubic spline is
+    used; the tails are approximated by a location-scale family.
 License: GPL (>= 3)
-Encoding: UTF-8
-LazyData: true
-Roxygen: list(markdown = TRUE)
-RoxygenNote: 7.2.3
-Suggests: 
-    knitr,
-    rmarkdown,
-    dplyr,
-    ggplot2,
-    testthat (>= 3.0.0)
+URL: http://reichlab.io/distfromq/
 Imports: 
     checkmate,
     purrr,
     splines,
+    stats,
+    utils,
     zeallot
-VignetteBuilder: knitr
+Suggests: 
+    dplyr,
+    ggplot2,
+    knitr,
+    rmarkdown,
+    testthat (>= 3.0.0)
+VignetteBuilder: 
+    knitr
 Config/testthat/edition: 3
-URL: http://reichlab.io/distfromq/
+Encoding: UTF-8
+LazyData: true
+Roxygen: list(markdown = TRUE)
+RoxygenNote: 7.3.1

R/ext.R

@@ -1,3 +1,5 @@
+a <- b <- NULL
+
 #' Calculate location and scale parameters for a specified distribution so that
 #' it matches two specified quantiles
 #'
@@ -14,18 +16,18 @@
 #' @return named list with entries `"a"`, the location parameter, and `"b"`, the
 #'   scale parameter
 calc_loc_scale_params <- function(ps, qs, dist) {
-    if (dist == "lnorm") {
-        if (any(qs <= 0.0)) {
-            stop("For dist = 'lnorm', all qs must be positive")
-        }
-        qs <- log(qs)
-        qdst <- qnorm
-    } else {
-        qdst <- get(paste0("q", dist))
+  if (dist == "lnorm") {
+    if (any(qs <= 0.0)) {
+      stop("For dist = 'lnorm', all qs must be positive")
     }
-    b <- suppressWarnings((qs[2] - qs[1]) / (qdst(ps[2]) - qdst(ps[1])))
-    a <- suppressWarnings(qs[1] - b * qdst(ps[1]))
-    return(list(a = a, b = b))
+    qs <- log(qs)
+    qdst <- qnorm
+  } else {
+    qdst <- get(paste0("q", dist))
+  }
+  b <- suppressWarnings((qs[2] - qs[1]) / (qdst(ps[2]) - qdst(ps[1])))
+  a <- suppressWarnings(qs[1] - b * qdst(ps[1]))
+  return(list(a = a, b = b))
 }
 
 
@@ -47,25 +49,25 @@ calc_loc_scale_params <- function(ps, qs, dist) {
 #'   specified location-scale family that has quantiles matching those in `ps`
 #'   and `qs`
 d_ext_factory <- function(ps, qs, dist) {
-    c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
+  c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
 
-    if (dist == "lnorm") {
-        d_ext <- function(x, log = FALSE) {
-            return(dlnorm(x, meanlog = a, sdlog = b, log = log))
-        }
-    } else {
-        ddst <- get(paste0("d", dist))
-        d_ext <- function(x, log = FALSE) {
-            result <- ddst((x - a) / b, log = TRUE) - log(b)
-            if (log) {
-                return(result)
-            } else {
-                return(exp(result))
-            }
-        }
+  if (dist == "lnorm") {
+    d_ext <- function(x, log = FALSE) {
+      return(dlnorm(x, meanlog = a, sdlog = b, log = log))
     }
+  } else {
+    ddst <- get(paste0("d", dist))
+    d_ext <- function(x, log = FALSE) {
+      result <- ddst((x - a) / b, log = TRUE) - log(b)
+      if (log) {
+        return(result)
+      } else {
+        return(exp(result))
+      }
+    }
+  }
 
-    return(d_ext)
+  return(d_ext)
 }
 
 
@@ -87,21 +89,21 @@ d_ext_factory <- function(ps, qs, dist) {
 #'   distribution in the specified location-scale family that has quantiles
 #'   matching those in `ps` and `qs`
 p_ext_factory <- function(ps, qs, dist) {
-    c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
+  c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
 
-    if (dist == "lnorm") {
-        p_ext <- function(q, log.p = FALSE) {
-            return(plnorm(q, meanlog = a, sdlog = b, log.p = log.p))
-        }
-    } else {
-        pdst <- get(paste0("p", dist))
+  if (dist == "lnorm") {
+    p_ext <- function(q, log.p = FALSE) {
+      return(plnorm(q, meanlog = a, sdlog = b, log.p = log.p))
+    }
+  } else {
+    pdst <- get(paste0("p", dist))
 
-        p_ext <- function(q, log.p = FALSE) {
-            return(pdst((q - a) / b, log.p = log.p))
-        }
+    p_ext <- function(q, log.p = FALSE) {
+      return(pdst((q - a) / b, log.p = log.p))
     }
+  }
 
-    return(p_ext)
+  return(p_ext)
 }
 
 
@@ -122,25 +124,25 @@ p_ext_factory <- function(ps, qs, dist) {
 #'   quantile function of the distribution in the specified location-scale
 #'   family that has quantiles matching those in `ps` and `qs`
 q_ext_factory <- function(ps, qs, dist) {
-    c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
+  c(a, b) %<-% calc_loc_scale_params(ps, qs, dist)
 
-    if (dist == "lnorm") {
-        q_ext <- function(p) {
-            return(qlnorm(p, meanlog = a, sdlog = b))
-        }
-    } else {
-        qdst <- get(paste0("q", dist))
+  if (dist == "lnorm") {
+    q_ext <- function(p) {
+      return(qlnorm(p, meanlog = a, sdlog = b))
+    }
+  } else {
+    qdst <- get(paste0("q", dist))
 
-        if (b == 0) {
-            q_ext <- function(p) {
-                rep(a, length(p))
-            }
-        } else {
-            q_ext <- function(p) {
-                return(a + b * qdst(p))
-            }
-        }
+    if (b == 0) {
+      q_ext <- function(p) {
+        rep(a, length(p))
+      }
+    } else {
+      q_ext <- function(p) {
+        return(a + b * qdst(p))
+      }
     }
+  }
 
-    return(q_ext)
+  return(q_ext)
 }