version 0.3.0

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

@@ -1,4 +1,4 @@
-# Workflow derived from https://github.com/r-lib/actions/tree/master/examples
+# 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:
@@ -18,7 +18,7 @@ jobs:
       fail-fast: false
       matrix:
         config:
-          - {os: macOS-latest,   r: 'release'}
+          - {os: macos-latest,   r: 'release'}
           - {os: windows-latest, r: 'release'}
           - {os: ubuntu-latest,   r: 'devel', http-user-agent: 'release'}
           - {os: ubuntu-latest,   r: 'release'}
@@ -29,30 +29,21 @@ jobs:
       R_KEEP_PKG_SOURCE: yes
 
     steps:
-      - uses: actions/checkout@v2
+      - uses: actions/checkout@v3
 
-      - uses: r-lib/actions/setup-pandoc@v1
+      - uses: r-lib/actions/setup-pandoc@v2
 
-      - uses: r-lib/actions/setup-r@v1
+      - 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@v1
+      - uses: r-lib/actions/setup-r-dependencies@v2
         with:
-          extra-packages: rcmdcheck
+          extra-packages: any::rcmdcheck
+          needs: check
 
-      - uses: r-lib/actions/check-r-package@v1
-
-      - name: Show testthat output
-        if: always()
-        run: find check -name 'testthat.Rout*' -exec cat '{}' \; || true
-        shell: bash
-
-      - name: Upload check results
-        if: failure()
-        uses: actions/upload-artifact@main
+      - uses: r-lib/actions/check-r-package@v2
         with:
-          name: ${{ runner.os }}-r${{ matrix.config.r }}-results
-          path: check
+          upload-snapshots: true

.github/workflows/test-coverage.yaml

@@ -0,0 +1,50 @@
+# 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: test-coverage
+
+jobs:
+  test-coverage:
+    runs-on: ubuntu-latest
+    env:
+      GITHUB_PAT: ${{ secrets.GITHUB_TOKEN }}
+
+    steps:
+      - uses: actions/checkout@v3
+
+      - uses: r-lib/actions/setup-r@v2
+        with:
+          use-public-rspm: true
+
+      - uses: r-lib/actions/setup-r-dependencies@v2
+        with:
+          extra-packages: any::covr
+          needs: coverage
+
+      - name: Test coverage
+        run: |
+          covr::codecov(
+            quiet = FALSE,
+            clean = FALSE,
+            install_path = file.path(Sys.getenv("RUNNER_TEMP"), "package")
+          )
+        shell: Rscript {0}
+
+      - name: Show testthat output
+        if: always()
+        run: |
+          ## --------------------------------------------------------------------
+          find ${{ runner.temp }}/package -name 'testthat.Rout*' -exec cat '{}' \; || true
+        shell: bash
+
+      - name: Upload test results
+        if: failure()
+        uses: actions/upload-artifact@v3
+        with:
+          name: coverage-test-failures
+          path: ${{ runner.temp }}/package

.gitignore

@@ -1,2 +1,5 @@
 inst/doc
 .Rproj.user
+
+*.o
+*.so

DESCRIPTION

@@ -1,23 +1,31 @@
 Package: eppverification
 Type: Package
 Title: Verification Tools for the Statistical Postprocessing of Ensemble Forecasts 
-Version: 0.2.0
+Version: 0.3.0
 Authors@R: c(
     person(given = "David",
            family = "Jobst",
            role = c("aut", "cre"),
-           email = "jobst@imai.uni-hildesheim.de",
+           email = "jobstd@uni-hildesheim.de",
            comment = c(DOI = "10.5281/zenodo.5574572")))
-Maintainer: David Jobst <jobst@imai.uni-hildesheim.de>
+Maintainer: David Jobst <jobstd@uni-hildesheim.de>
 Description: This package provides user-friendly univariate and multivariate verification tools for the statistical ensemble post-processing. It allows to score and assess the calibration (reliability) and sharpness of ensemble forecasts and predictive distributions. In addition this package can be used to create useful contemporary visualizations for verification.
 URL: https://github.com/jobstdavid/eppverification
 BugReports: https://github.com/jobstdavid/eppverification/issues
-Imports: ggplot2, ggmap, fields, vegan, pcaPP
+Imports: 
+    ggplot2,
+    fields,
+    vegan,
+    pcaPP,
+    Rfast,
+    Rcpp
 License: GPL (>= 3) + file LICENSE
 Encoding: UTF-8
 LazyData: true
-RoxygenNote: 7.1.2
+RoxygenNote: 7.2.3
 Suggests: 
     knitr,
     rmarkdown,
     testthat (>= 3.0.0)
+LinkingTo: 
+    Rcpp, RcppArmadillo

NAMESPACE

@@ -1,7 +1,7 @@
 # Generated by roxygen2: do not edit by hand
 
 export(ae)
-export(box.plot)
+export(bh.test)
 export(bs)
 export(cov.plot)
 export(cpi)
@@ -16,7 +16,6 @@ export(es)
 export(line.plot)
 export(logs)
 export(m.pit)
-export(map.plot)
 export(ment)
 export(mri)
 export(mrnk)
@@ -28,18 +27,22 @@ export(rmv)
 export(rnk)
 export(score.plot)
 export(se)
+export(ss)
 export(var.pit)
 export(vr.hist)
 export(vs)
+importFrom(Rcpp,sourceCpp)
+importFrom(Rfast,colmeans)
+importFrom(Rfast,cova)
+importFrom(Rfast,rowMedians)
+importFrom(Rfast,rowVars)
+importFrom(Rfast,rowmeans)
+importFrom(Rfast,rowsums)
 importFrom(fields,rdist)
-importFrom(ggmap,calc_zoom)
-importFrom(ggmap,get_stamenmap)
-importFrom(ggmap,ggmap)
-importFrom(ggmap,make_bbox)
 importFrom(ggplot2,aes)
+importFrom(ggplot2,after_stat)
 importFrom(ggplot2,element_text)
 importFrom(ggplot2,geom_abline)
-importFrom(ggplot2,geom_boxplot)
 importFrom(ggplot2,geom_histogram)
 importFrom(ggplot2,geom_hline)
 importFrom(ggplot2,geom_line)
@@ -52,23 +55,22 @@ importFrom(ggplot2,ggtitle)
 importFrom(ggplot2,labs)
 importFrom(ggplot2,scale_color_manual)
 importFrom(ggplot2,scale_fill_gradient)
-importFrom(ggplot2,scale_fill_manual)
 importFrom(ggplot2,scale_linetype_manual)
-importFrom(ggplot2,scale_shape_manual)
-importFrom(ggplot2,scale_size_manual)
 importFrom(ggplot2,scale_x_continuous)
 importFrom(ggplot2,scale_x_discrete)
 importFrom(ggplot2,scale_y_continuous)
 importFrom(ggplot2,scale_y_discrete)
-importFrom(ggplot2,stat)
 importFrom(ggplot2,theme)
+importFrom(ggplot2,theme_bw)
 importFrom(ggplot2,xlab)
 importFrom(ggplot2,ylab)
 importFrom(pcaPP,l1median_VaZh)
 importFrom(stats,acf)
 importFrom(stats,complete.cases)
 importFrom(stats,median)
-importFrom(stats,pnorm)
+importFrom(stats,na.omit)
+importFrom(stats,pt)
 importFrom(stats,setNames)
 importFrom(stats,var)
 importFrom(vegan,spantree)
+useDynLib(eppverification, .registration = TRUE)

NEWS.md

@@ -1,3 +1,15 @@
+# eppverification 0.3.0 (September 30, 2023)
+
+- univariate and multivariate score calculation is speeded-up using C++ code by the R-packages `Rfast`, `Rcpp`, `RcppArmadillo`.
+- new function `bh.test` to perform a Benjamini-Hochberg-Correction for different p-values.
+- new function `ss` to calculate the skill score.
+- fast calculation of the sample covariance matrix for the determinate sharpness `ds`.
+- change test statistic in `dm.test`. 
+- better handling of NA values in the verification functions.
+- changed `stat` to `after_stat` in `ggplot2` based functions.
+- removed the functions `map.plot` and `box.plot`. 
+
+
 # eppverification 0.2.0 (Januar 9, 2022)
 
 - new function `dm.test` to perform a Diebold-Mariano-Test for two forecasts.

R/RcppExports.R

@@ -0,0 +1,35 @@
+# Generated by using Rcpp::compileAttributes() -> do not edit by hand
+# Generator token: 10BE3573-1514-4C36-9D1C-5A225CD40393
+
+crps_cpp <- function(y, x) {
+    .Call(`_eppverification_crps_cpp`, y, x)
+}
+
+crps_sml_cpp <- function(y, x) {
+    .Call(`_eppverification_crps_sml_cpp`, y, x)
+}
+
+crps_mc_cpp <- function(y, x) {
+    .Call(`_eppverification_crps_mc_cpp`, y, x)
+}
+
+euclnorm_cpp <- function(x) {
+    .Call(`_eppverification_euclnorm_cpp`, x)
+}
+
+es_cpp <- function(y, x) {
+    .Call(`_eppverification_es_cpp`, y, x)
+}
+
+es_mc_cpp <- function(y, x) {
+    .Call(`_eppverification_es_mc_cpp`, y, x)
+}
+
+vs_cpp <- function(y, x, w, p) {
+    .Call(`_eppverification_vs_cpp`, y, x, w, p)
+}
+
+ds_cpp <- function(x) {
+    .Call(`_eppverification_ds_cpp`, x)
+}
+

R/ae.R

@@ -5,6 +5,7 @@
 #' @param y vector of observations
 #' @param x matrix of ensemble forecasts/samples of a predictive distribution or vector of medians of ensemble forecasts/a predictive distribution (depending on \code{y}; see details)
 #' @param mean logical; if \code{TRUE} the mean of the AE values is calculated for output; if \code{FALSE} the single AE values are used as output; default: \code{FALSE}
+#' @param na.rm logical; if \code{TRUE} NA are removed after the computation; if \code{FALSE} NA are used in the computation; default: \code{FALSE}
 #'
 #' @details
 #' For a vector \code{y} of length n, \code{x} can be given as matrix of ensemble forecasts/samples of a predictive distribution
@@ -15,7 +16,6 @@
 #' If the medians of ensemble forecasts or of a predictive distribution are directly
 #' available, \code{x} can be given as vector of medians, where
 #' the i-th entry of \code{y} belongs to the i-th entry of \code{x}.
-#' Only finite values of \code{y} and \code{x} are used.
 #'
 #' In addition, with this function, the Mean Absolute Error (MAE) can be calculated.
 #'
@@ -46,50 +46,41 @@
 #'
 #' @rdname ae
 #'
-#' @importFrom stats median
+#' @importFrom stats median na.omit
+#' @importFrom Rfast rowMedians
+#'
 #' @export
-ae <- function(y, x, mean = FALSE) {
+ae <- function(y, x, mean = FALSE, na.rm = FALSE) {
   if (!is.vector(y)) {
     stop("'y' should be a vector!")
   }
   if (is.matrix(x)) {
     if (length(y) != nrow(x)) {
       stop("Length of 'y' is not equal to the number of rows of 'x'!")
     }
-    index <- which(is.finite(y))
-    y <- y[index]
-    x <- x[index, ]
 
-    med <- apply(x, 1, median.i)
+    med <- rowMedians(x = x, parallel = TRUE, na.rm = FALSE)
     ae.value <- abs(y-med)
   } else if (is.vector(x)) {
     if (length(y) != length(x)) {
       stop("Length of 'y' is not equal to the length of 'x'!")
     }
-    #prepare data
-    data <- cbind(y, x)
-    data <- matrix(data[apply(is.finite(data), 1, all), ], ncol = 2)
-    y <- data[, 1]
-    x <- data[, 2]
 
     ae.value <- abs(y-x)
   } else {
     stop("'x' should be a vector or matrix!")
   }
 
+  if (na.rm == TRUE) {
+    ae.value <- as.vector(na.omit(ae.value))
+  }
+
   if (mean == TRUE) {
     ae.value <- mean(ae.value)
   }
   return(as.numeric(ae.value))
 
 }
-#'
-#' internal function
-#' @noRd
-median.i <- function(z) {
-  z <- z[is.finite(z)]
-  out <- median(z)
-  return(out)
-}
+